【论文合集】Awesome Low Level Vision

Low-level和High-level任务

Low-level任务：常见的包括 Super-Resolution，denoise， deblur， dehze， low-light enhancement， deartifacts等。简单来说，是把特定降质下的图片还原成好看的图像，现在基本上用end-to-end的模型来学习这类 ill-posed问题的求解过程，客观指标主要是PSNR，SSIM，大家指标都刷的很高。目前面临以下几点问题：

• 泛化性差，换个数据集，同种任务变现就很差。
• 客观指标与主观感受存在，GAP。
• 落地的问题，SOTA模型运算量很(上百G Flops)，但实际不可能这么用。
• 偏向于解决实际问题，主要是为人服务，如手机里的各类夜景模式、美化等，都会用到相关算法。
• 市面上公司做 low-level 比较多的是手机厂商（华米OV）、安防（海康大华），相机（大疆，ISP厂商）、无人机（大疆）、视频网站（B站，快手等）。一般涉及到图像、视频增强的场景都是low-level试用的问题。

High-level任务：分类，检测，分割等。一般公开训练数据都是高品质的图像，当送入降质图像时，性能会有下降，即使网络已经经过大量的数据增强（形状，亮度，色度等变换）。真实应用场景是不可能像训练集那样完美的，采集图像的过程中会面临各种降质问题，需要两者来结合。简单来说，结合的方式分为以下几种

• 直接在降质图像上fine-tuning
• 先经过low-level的增强网络，再送入High-level的模型，两者分开训练
• 将增强网络和高层模型（如分类）联合训练

CVPR2023-Low-Level-Vision

Image Restoration - 图像恢复

Efficient and Explicit Modelling of Image Hierarchies for Image Restoration

• Paper: https://arxiv.org/abs/2303.00748
• Code: GitHub - ofsoundof/GRL-Image-Restoration
• Tags: Transformer

Learning Distortion Invariant Representation for Image Restoration from A Causality Perspective

• Paper: https://arxiv.org/abs/2303.06859
• Code: https://github.com/lixinustc/Casual-IRDIL

Generative Diffusion Prior for Unified Image Restoration and Enhancement

• Paper: https://arxiv.org/abs/2304.01247
• Code: https://github.com/Fayeben/GenerativeDiffusionPrior

Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bank

• Paper: https://arxiv.org/abs/2303.09101
• Code: https://github.com/Huang-ShiRui/Semi-UIR
• Tags: Underwater Image Restoration

Nighttime Smartphone Reflective Flare Removal Using Optical Center Symmetry Prior

• Paper: https://arxiv.org/abs/2303.15046
• Code: https://github.com/ykdai/BracketFlare
• Tags: Reflective Flare Removal

Image Reconstruction

Raw Image Reconstruction with Learned Compact Metadata

• Paper: https://arxiv.org/abs/2302.12995
• Code: GitHub - wyf0912/R2LCM: [CVPR 2023] Raw Image Reconstruction with Learned Compact Metadata

High-resolution image reconstruction with latent diffusion models from human brain activity

• Paper: High-resolution image reconstruction with latent diffusion models from human brain activity | bioRxiv
• Code: GitHub - yu-takagi/StableDiffusionReconstruction: Takagi and Nishimoto, CVPR 2023

DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration

• Paper: https://arxiv.org/abs/2303.06885

Burst Restoration

Burstormer: Burst Image Restoration and Enhancement Transformer

• Paper: https://arxiv.org/abs/2304.01194
• Code: GitHub - akshaydudhane16/Burstormer

Video Restoration

Blind Video Deflickering by Neural Filtering with a Flawed Atlas

• Paper: https://arxiv.org/abs/2303.08120
• Code: GitHub - ChenyangLEI/All-In-One-Deflicker: [CVPR2023] Blind Video Deflickering by Neural Filtering with a Flawed Atlas
• Tags: Deflickering

Super Resolution - 超分辨率

Image Super Resolution

Activating More Pixels in Image Super-Resolution Transformer

• Paper: https://arxiv.org/abs/2205.04437
• Code: https://github.com/XPixelGroup/HAT
• Tags: Transformer

N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution

• Paper: https://arxiv.org/abs/2211.11436
• Code: https://github.com/rami0205/NGramSwin

Omni Aggregation Networks for Lightweight Image Super-Resolution

• Paper:
• Code: GitHub - Francis0625/Omni-SR: [CVPR2023] Implementation of ''Omni Aggregation Networks for Lightweight Image Super-Resolution".

OPE-SR: Orthogonal Position Encoding for Designing a Parameter-free Upsampling Module in Arbitrary-scale Image Super-Resolution

• Paper: https://arxiv.org/abs/2303.01091

Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution

• Paper: https://arxiv.org/abs/2303.05156

Super-Resolution Neural Operator

• Paper: https://arxiv.org/abs/2303.02584
• Code: https://github.com/2y7c3/Super-Resolution-Neural-Operator

Human Guided Ground-truth Generation for Realistic Image Super-resolution

• Paper: https://arxiv.org/abs/2303.13069
• Code: https://github.com/ChrisDud0257/PosNegGT

Implicit Diffusion Models for Continuous Super-Resolution

• Paper: https://arxiv.org/abs/2303.16491
• Code: https://github.com/Ree1s/IDM

Zero-Shot Dual-Lens Super-Resolution

• Paper:
• Code: https://github.com/XrKang/ZeDuSR

Learning Generative Structure Prior for Blind Text Image Super-resolution

• Paper: https://arxiv.org/abs/2303.14726
• Code: https://github.com/csxmli2016/MARCONet
• Tags: Text SR

Guided Depth Super-Resolution by Deep Anisotropic Diffusion

• Paper: https://arxiv.org/abs/2211.11592
• Code: GitHub - prs-eth/Diffusion-Super-Resolution: [CVPR 2023] Guided Depth Super-Resolution by Deep Anisotropic Diffusion
• Tags: Guided Depth SR

Video Super Resolution

Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting

• Paper: https://arxiv.org/abs/2303.08331
• Code: coulsonlee/STDO-CVPR2023 · GitHub

Structured Sparsity Learning for Efficient Video Super-Resolution

• Paper: https://github.com/Zj-BinXia/SSL
• Code: https://arxiv.org/abs/2206.07687

Image Rescaling - 图像缩放

HyperThumbnail: Real-time 6K Image Rescaling with Rate-distortion Optimization

• Paper: https://arxiv.org/abs/2304.01064
• Code: GitHub - AbnerVictor/HyperThumbnail: [CVPR 2023] HyperThumbnail: Real-time 6K Image Rescaling with Rate-distortion Optimization. Official implementation.

Denoising - 去噪

Image Denoising

Masked Image Training for Generalizable Deep Image Denoising

• Paper: https://arxiv.org/abs/2303.13132
• Code: https://github.com/haoyuc/MaskedDenoising

Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising

• Paper: https://arxiv.org/abs/2303.14934
• Cdoe: https://github.com/nagejacob/SpatiallyAdaptiveSSID
• Tags: Self-Supervised

LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising

• Paper: https://arxiv.org/abs/2304.00534
• Code: https://github.com/Wang-XIaoDingdd/LGBPN
• Tags: Self-Supervised

Real-time Controllable Denoising for Image and Video

• Paper: https://arxiv.org/pdf/2303.16425.pdf

Deblurring - 去模糊

Image Deblurring

Structured Kernel Estimation for Photon-Limited Deconvolution

• Paper: https://arxiv.org/abs/2303.03472
• Code: https://github.com/sanghviyashiitb/structured-kernel-cvpr23

Blur Interpolation Transformer for Real-World Motion from Blur

• Paper: https://arxiv.org/abs/2211.11423
• Code: https://github.com/zzh-tech/BiT

Neumann Network with Recursive Kernels for Single Image Defocus Deblurring

• Paper:
• Code: https://github.com/csZcWu/NRKNet

Efficient Frequency Domain-based Transformers for High-Quality Image Deblurring

• Paper: https://arxiv.org/abs/2211.12250
• Code: GitHub - kkkls/FFTformer

Deraining - 去雨

Learning A Sparse Transformer Network for Effective Image Deraining

• Paper: https://arxiv.org/abs/2303.11950
• Code: https://github.com/cschenxiang/DRSformer

Dehazing - 去雾

RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors

• Paper:
• Code: GitHub - RQ-Wu/RIDCP_dehazing: [CVPR 2023] | RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors

Curricular Contrastive Regularization for Physics-aware Single Image Dehazing

• Paper: https://arxiv.org/abs/2303.14218
• Code: GitHub - YuZheng9/C2PNet: [CVPR 2023] Curricular Contrastive Regularization for Physics-aware Single Image Dehazing

Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Prior

• Paper: https://arxiv.org/abs/2303.09757
• Code: https://github.com/jiaqixuac/MAP-Net

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

Learning a Practical SDR-to-HDRTV Up-conversion using New Dataset and Degradation Models

• Paper: https://arxiv.org/abs/2303.13031
• Code: https://github.com/AndreGuo/HDRTVDM

Frame Interpolation - 插帧

Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation

• Paper: https://arxiv.org/abs/2303.00440
• Code: GitHub - MCG-NJU/EMA-VFI: [CVPR 2023] Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolatio

A Unified Pyramid Recurrent Network for Video Frame Interpolation

• Paper: https://arxiv.org/abs/2211.03456
• Code: GitHub - srcn-ivl/UPR-Net: Official implementation of our CVPR2023 paper "A Unified Pyramid Recurrent Network for Video Frame Interpolation"

BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation

• Paper: https://arxiv.org/abs/2304.02225
• Code: GitHub - JunHeum/BiFormer: BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation, CVPR2023

Event-based Video Frame Interpolation with Cross-Modal Asymmetric Bidirectional Motion Fields

• Paper:
• Code: GitHub - intelpro/CBMNet: Official repository of "Event-based Video Frame Interpolation with Cross-Modal Asymmetric Bidirectional Motion Fields", CVPR 2023 paper
• Tags: Event-based

Event-based Blurry Frame Interpolation under Blind Exposure

• Paper:
• Code: GitHub - WarranWeng/EBFI-BE: Event-based Blurry Frame Interpolation under Blind Exposure, CVPR2023
• Tags: Event-based

Joint Video Multi-Frame Interpolation and Deblurring under Unknown Exposure Time

• Paper: https://arxiv.org/abs/2303.15043
• Code: GitHub - shangwei5/VIDUE: Joint Video Multi-Frame Interpolation and Deblurring under Unknown Exposure Time (CVPR2023)
• Tags: Frame Interpolation and Deblurring

Image Enhancement - 图像增强

Low-Light Image Enhancement

Learning Semantic-Aware Knowledge Guidance for Low-Light Image Enhancement

• Paper:
• Code: https://github.com/langmanbusi/Semantic-Aware-Low-Light-Image-Enhancement

Visibility Constrained Wide-band Illumination Spectrum Design for Seeing-in-the-Dark

• Paper: https://arxiv.org/abs/2303.11642
• Code: https://github.com/MyNiuuu/VCSD
• Tags: NIR2RGB

Image Matting - 图像抠图

Referring Image Matting

• Paper: https://arxiv.org/abs/2206.05149
• Code: GitHub - JizhiziLi/RIM: [CVPR 2023] Referring Image Matting

Shadow Removal - 阴影消除

ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removal

• Paper: https://arxiv.org/abs/2212.04711
• Code: https://github.com/GuoLanqing/ShadowDiffusion

Image Compression - 图像压缩

Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger

• Paper: https://arxiv.org/abs/2302.14677

Context-based Trit-Plane Coding for Progressive Image Compression

• Paper: https://arxiv.org/abs/2303.05715
• Code: https://github.com/seungminjeon-github/CTC

Learned Image Compression with Mixed Transformer-CNN Architectures

• Paper: https://arxiv.org/abs/2303.14978
• Code: GitHub - jmliu206/LIC_TCM

Video Compression

Neural Video Compression with Diverse Contexts

• Paper: https://github.com/microsoft/DCVC
• Code: https://arxiv.org/abs/2302.14402

Image Quality Assessment - 图像质量评价

Quality-aware Pre-trained Models for Blind Image Quality Assessment

• Paper: https://arxiv.org/abs/2303.00521

Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective

• Paper: https://arxiv.org/abs/2303.14968
• Code: GitHub - zwx8981/LIQE

Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Method

• Paper: https://arxiv.org/abs/2303.15166
• Code: GitHub - Dreemurr-T/BAID

Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild

• Paper: https://arxiv.org/abs/2304.00451

Style Transfer - 风格迁移

Fix the Noise: Disentangling Source Feature for Controllable Domain Translation

• Paper: https://arxiv.org/abs/2303.11545
• Code: https://github.com/LeeDongYeun/FixNoise

Neural Preset for Color Style Transfer

• Paper: https://arxiv.org/abs/2303.13511
• Code: https://github.com/ZHKKKe/NeuralPreset

CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer

• Paper: https://arxiv.org/abs/2303.17867

StyleGAN Salon: Multi-View Latent Optimization for Pose-Invariant Hairstyle Transfer

• Paper: https://arxiv.org/abs/2304.02744
• Project: StyleGANSalon

Image Editing - 图像编辑

Imagic: Text-Based Real Image Editing with Diffusion Models

• Paper: https://arxiv.org/abs/2210.09276

SINE: SINgle Image Editing with Text-to-Image Diffusion Models

• Paper: https://arxiv.org/abs/2212.04489
• Code: https://github.com/zhang-zx/SINE

CoralStyleCLIP: Co-optimized Region and Layer Selection for Image Editing

• Paper: https://arxiv.org/abs/2303.05031

DeltaEdit: Exploring Text-free Training for Text-Driven Image Manipulation

• Paper: https://arxiv.org/abs/2303.06285
• Code: https://arxiv.org/abs/2303.06285

SIEDOB: Semantic Image Editing by Disentangling Object and Background

• Paper: https://arxiv.org/abs/2303.13062
• Code: GitHub - WuyangLuo/SIEDOB

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

Multi-Concept Customization of Text-to-Image Diffusion

• Paper: https://arxiv.org/abs/2212.04488
• Code: GitHub - adobe-research/custom-diffusion: Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)

GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis

• Paper: https://arxiv.org/abs/2301.12959
• Code: GitHub - tobran/GALIP: [CVPR2023] A faster, smaller, and better text-to-image model for large-scale training

Scaling up GANs for Text-to-Image Synthesis

• Paper: https://arxiv.org/abs/2303.05511
• Project: GigaGAN: Scaling up GANs for Text-to-Image Synthesis

MAGVLT: Masked Generative Vision-and-Language Transformer

• Paper: https://arxiv.org/abs/2303.12208

Freestyle Layout-to-Image Synthesis

• Paper: https://arxiv.org/abs/2303.14412
• Code: GitHub - essunny310/FreestyleNet: [CVPR 2023 Highlight] Freestyle Layout-to-Image Synthesis

Variational Distribution Learning for Unsupervised Text-to-Image Generation

• Paper: https://arxiv.org/abs/2303.16105

Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment

• Paper: https://arxiv.org/abs/2303.17490
• Project: Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment

Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation

• Paper: https://arxiv.org/abs/2304.01816

Image-to-Image / Image Guided

LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data

• Paper: https://arxiv.org/abs/2208.14889
• Code: GitHub - KU-CVLAB/LANIT: Official repository for LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data (CVPR 2023)

Person Image Synthesis via Denoising Diffusion Model

• Paper: https://arxiv.org/abs/2211.12500
• Code: https://github.com/ankanbhunia/PIDM

Picture that Sketch: Photorealistic Image Generation from Abstract Sketches

• Paper: https://arxiv.org/abs/2303.11162

Fine-Grained Face Swapping via Regional GAN Inversion

• Paper: https://arxiv.org/abs/2211.14068
• Code: https://github.com/e4s2022/e4s

Masked and Adaptive Transformer for Exemplar Based Image Translation

• Paper: https://arxiv.org/abs/2303.17123
• Code: GitHub - AiArt-HDU/MATEBIT: Source code of "Masked and Adaptive Transformer for Exemplar Based Image Translation", accepted by CVPR 2023.

Zero-shot Generative Model Adaptation via Image-specific Prompt Learning

• Paper: https://arxiv.org/abs/2304.03119
• Code: GitHub - Picsart-AI-Research/IPL-Zero-Shot-Generative-Model-Adaptation: [CVPR 2023] Zero-shot Generative Model Adaptation via Image-specific Prompt Learning

Others for image generation

AdaptiveMix: Robust Feature Representation via Shrinking Feature Space

• Paper: https://arxiv.org/abs/2303.01559
• Code: GitHub - WentianZhang-ML/AdaptiveMix: This is an official pytorch implementation of 'AdaptiveMix: Robust Feature Representation via Shrinking Feature Space' (accepted by CVPR2023).

MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis

• Paper: https://arxiv.org/abs/2211.09117
• Code: GitHub - LTH14/mage: A PyTorch implementation of MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis

Regularized Vector Quantization for Tokenized Image Synthesis

• Paper: https://arxiv.org/abs/2303.06424

Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization

• Paper:
• Code: https://github.com/CrossmodalGroup/DynamicVectorQuantization

Not All Image Regions Matter: Masked Vector Quantization for Autoregressive Image Generation

• Paper:
• Code: https://github.com/CrossmodalGroup/MaskedVectorQuantization

Exploring Incompatible Knowledge Transfer in Few-shot Image Generation

• Paper:
• Code: GitHub - yunqing-me/RICK: The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Post-training Quantization on Diffusion Models

• Paper: https://arxiv.org/abs/2211.15736
• Code: GitHub - 42Shawn/PTQ4DM: Implementation of Post-training Quantization on Diffusion Models (CVPR 2023)

LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation

• Paper: https://arxiv.org/abs/2303.17189
• Code: GitHub - ZGCTroy/LayoutDiffusion

DiffCollage: Parallel Generation of Large Content with Diffusion Models

• Paper: https://arxiv.org/abs/2303.17076
• Project: DiffCollage: Parallel Generation of Large Content with Diffusion Models

Few-shot Semantic Image Synthesis with Class Affinity Transfer

• Paper: https://arxiv.org/abs/2304.02321

Video Generation

Conditional Image-to-Video Generation with Latent Flow Diffusion Models

• Paper: https://arxiv.org/abs/2303.13744
• Code: GitHub - nihaomiao/CVPR23_LFDM: The pytorch implementation of our CVPR 2023 paper "Conditional Image-to-Video Generation with Latent Flow Diffusion Models"

Video Probabilistic Diffusion Models in Projected Latent Space

• Paper: https://arxiv.org/abs/2302.07685
• Code: https://github.com/sihyun-yu/PVDM

DPE: Disentanglement of Pose and Expression for General Video Portrait Editing

• Paper: https://arxiv.org/abs/2301.06281
• Code: GitHub - Carlyx/DPE: [CVPR 2023] DPE: Disentanglement of Pose and Expression for General Video Portrait Editing

Decomposed Diffusion Models for High-Quality Video Generation

• Paper: https://arxiv.org/abs/2303.08320

Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding

• Paper: https://arxiv.org/abs/2212.02802
• Code: GitHub - man805/Diffusion-Video-Autoencoders: An official implementation of "Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding" (CVPR 2023) in PyTorch.

MoStGAN: Video Generation with Temporal Motion Styles

• Paper:
• Code: https://github.com/xiaoqian-shen/MoStGAN

Others

DC2: Dual-Camera Defocus Control by Learning to Refocus

• Paper: https://arxiv.org/abs/2304.03285
• Project: DC2: Dual-Camera Defocus Control by Learning to Refocus

Images Speak in Images: A Generalist Painter for In-Context Visual Learning

• Paper: https://arxiv.org/abs/2212.02499
• Code: https://github.com/baaivision/Painter

Unifying Layout Generation with a Decoupled Diffusion Model

• Paper: https://arxiv.org/abs/2303.05049

Unsupervised Domain Adaption with Pixel-level Discriminator for Image-aware Layout Generation

• Paper: https://arxiv.org/abs/2303.14377

PosterLayout: A New Benchmark and Approach for Content-aware Visual-Textual Presentation Layout

• Paper: https://arxiv.org/abs/2303.15937
• Code: https://github.com/PKU-ICST-MIPL/PosterLayout-CVPR2023

LayoutDM: Discrete Diffusion Model for Controllable Layout Generation

• Paper: https://arxiv.org/abs/2303.08137
• Code: https://github.com/CyberAgentAILab/layout-dm

Make-A-Story: Visual Memory Conditioned Consistent Story Generation

• Paper: https://arxiv.org/abs/2211.13319
• Code: https://github.com/ubc-vision/Make-A-Story

Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models

• Paper: https://arxiv.org/abs/2303.10774
• Code: mattolson93/cross_gan_auditing · GitHub

LightPainter: Interactive Portrait Relighting with Freehand Scribble

• Paper: https://arxiv.org/abs/2303.12950
• Tags: Portrait Relighting

Neural Texture Synthesis with Guided Correspondence

• Paper:
• Code: https://github.com/EliotChenKJ/Guided-Correspondence-Loss
• Tags: Texture Synthesis

CF-Font: Content Fusion for Few-shot Font Generation

• Paper: https://arxiv.org/abs/2303.14017
• Code: https://github.com/wangchi95/CF-Font
• Tags: Font Generation

DeepVecFont-v2: Exploiting Transformers to Synthesize Vector Fonts with Higher Quality

• Paper: https://arxiv.org/abs/2303.14585
• Code: GitHub - yizhiwang96/deepvecfont-v2: [CVPR 2023] DeepVecFont-v2: Exploiting Transformers to Synthesize Vector Fonts with Higher Quality

Handwritten Text Generation from Visual Archetypes

• Paper: https://arxiv.org/abs/2303.15269
• Tags: Handwriting Generation

Disentangling Writer and Character Styles for Handwriting Generation

• Paper: https://arxiv.org/abs/2303.14736
• Code: GitHub - dailenson/SDT: This repository is the official implementation of Disentangling Writer and Character Styles for Handwriting Generation (CVPR23).
• Tags: Handwriting Generation

Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert

• Paper: https://arxiv.org/abs/2303.17480
• Code: GitHub - Sxjdwang/TalkLip

Uncurated Image-Text Datasets: Shedding Light on Demographic Bias

• Paper: https://arxiv.org/abs/2304.02828
• Code: https://github.com/noagarcia/phase

CVPR2022-Low-Level-Vision

Image Restoration - 图像恢复

Restormer: Efficient Transformer for High-Resolution Image Restoration

• Paper: https://arxiv.org/abs/2111.09881
• Code: https://github.com/swz30/Restormer
• Tags: Transformer

Uformer: A General U-Shaped Transformer for Image Restoration

• Paper: https://arxiv.org/abs/2106.03106
• Code: https://github.com/ZhendongWang6/Uformer
• Tags: Transformer

MAXIM: Multi-Axis MLP for Image Processing

• Paper: https://arxiv.org/abs/2201.02973
• Code: https://github.com/google-research/maxim
• Tags: MLP, also do image enhancement

All-In-One Image Restoration for Unknown Corruption

• Paper: http://pengxi.me/wp-content/uploads/2022/03/All-In-One-Image-Restoration-for-Unknown-Corruption.pdf
• Code: https://github.com/XLearning-SCU/2022-CVPR-AirNet

Fourier Document Restoration for Robust Document Dewarping and Recognition

• Paper: https://arxiv.org/abs/2203.09910
• Tags: Document Restoration

Exploring and Evaluating Image Restoration Potential in Dynamic Scenes

• Paper: https://arxiv.org/abs/2203.11754

ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image Prior

• Paper: https://arxiv.org/abs/2111.15362v2
• Code: https://github.com/ozgurkara99/ISNAS-DIP
• Tags: DIP, NAS

Deep Generalized Unfolding Networks for Image Restoration

• Paper: https://arxiv.org/abs/2204.13348
• Code: https://github.com/MC-E/Deep-Generalized-Unfolding-Networks-for-Image-Restoration

Attentive Fine-Grained Structured Sparsity for Image Restoration

• Paper: https://arxiv.org/abs/2204.12266
• Code: https://github.com/JungHunOh/SLS_CVPR2022

Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics

• Paper: CVPR 2022 Open Access Repository
• Tags: Self-Supervised

KNN Local Attention for Image Restoration

• Paper: CVPR 2022 Open Access Repository
• Code: https://sites.google.com/view/cvpr22-kit

GIQE: Generic Image Quality Enhancement via Nth Order Iterative Degradation

• Paper: CVPR 2022 Open Access Repository

TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions

• Paper: https://arxiv.org/abs/2111.14813
• Code: https://github.com/jeya-maria-jose/TransWeather
• Tags: Adverse Weather

Learning Multiple Adverse Weather Removal via Two-stage Knowledge Learning and Multi-contrastive Regularization: Toward a Unified Model

• Paper: https://openaccess.thecvf.com/content/CVPR2022/papers/Chen_Learning_Multiple_Adverse_Weather_Removal_via_Two-Stage_Knowledge_Learning_and_CVPR_2022_paper.pdf
• Code: https://github.com/fingerk28/Two-stage-Knowledge-For-Multiple-Adverse-Weather-Removal
• Tags: Adverse Weathe(deraining, desnowing, dehazing)

Rethinking Deep Face Restoration

• Paper: CVPR 2022 Open Access Repository
• Tags: Face

RestoreFormer: High-Quality Blind Face Restoration From Undegraded Key-Value Pairs

• Paper: CVPR 2022 Open Access Repository
• Code: https://github.com/wzhouxiff/RestoreFormer
• Tags: Face

Blind Face Restoration via Integrating Face Shape and Generative Priors

• Paper: CVPR 2022 Open Access Repository
• Tags: Face

End-to-End Rubbing Restoration Using Generative Adversarial Networks

• Paper: https://arxiv.org/abs/2205.03743
• Code: https://github.com/qingfengtommy/RubbingGAN
• Tags: [Workshop], Rubbing Restoration

GenISP: Neural ISP for Low-Light Machine Cognition

• Paper: https://arxiv.org/abs/2205.03688
• Tags: [Workshop], ISP

Burst Restoration

A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift

• Paper: https://arxiv.org/abs/2203.09294
• Code: GitHub - GuoShi28/2StageAlign: The official codes of our CVPR2022 paper: A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift
• Tags: joint denoising and demosaicking

Burst Image Restoration and Enhancement

• Paper: https://arxiv.org/abs/2110.03680
• Code: https://github.com/akshaydudhane16/BIPNet

Video Restoration

Revisiting Temporal Alignment for Video Restoration

• Paper: https://arxiv.org/abs/2111.15288
• Code: GitHub - redrock303/Revisiting-Temporal-Alignment-for-Video-Restoration

Neural Compression-Based Feature Learning for Video Restoration

• Paper:https://arxiv.org/abs/2203.09208

Bringing Old Films Back to Life

• Paper: https://arxiv.org/abs/2203.17276
• Code: https://github.com/raywzy/Bringing-Old-Films-Back-to-Life

Neural Global Shutter: Learn to Restore Video from a Rolling Shutter Camera with Global Reset Feature

• Paper: https://arxiv.org/abs/2204.00974
• Code: https://github.com/lightChaserX/neural-global-shutter
• Tags: restore clean global shutter (GS) videos

Context-Aware Video Reconstruction for Rolling Shutter Cameras

• Paper: https://arxiv.org/abs/2205.12912
• Code: https://github.com/GitCVfb/CVR
• Tags: Rolling Shutter Cameras

E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations

• Paper: https://arxiv.org/abs/2206.07578
• Tags: Event camera
• Withdrawal due to plagiarism

Hyperspectral Image Reconstruction

Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction

• Paper: https://arxiv.org/abs/2111.07910
• Code: https://github.com/caiyuanhao1998/MST

HDNet: High-resolution Dual-domain Learning for Spectral Compressive Imaging

• Paper: https://arxiv.org/abs/2203.02149

Super Resolution - 超分辨率

Image Super Resolution

Reflash Dropout in Image Super-Resolution

• Paper: https://arxiv.org/abs/2112.12089
• Code: https://github.com/Xiangtaokong/Reflash-Dropout-in-Image-Super-Resolution

Residual Local Feature Network for Efficient Super-Resolution

• Paper: https://arxiv.org/abs/2205.07514
• Code: https://github.com/fyan111/RLFN
• Tags: won the first place in the runtime track of the NTIRE 2022 efficient super-resolution challenge

Learning the Degradation Distribution for Blind Image Super-Resolution

• Paper: https://arxiv.org/abs/2203.04962
• Code: GitHub - greatlog/UnpairedSR: This is an offical implementation of the CVPR2022's paper Learning the Degradation Distribution for Blind Image Super-Resolution
• Tags: Blind SR

Deep Constrained Least Squares for Blind Image Super-Resolution

• Paper: https://arxiv.org/abs/2202.07508
• Code: GitHub - Algolzw/DCLS: "Deep Constrained Least Squares for Blind Image Super-Resolution", CVPR 2022.
• Tags: Blind SR

Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel

• Paper: https://arxiv.org/abs/2107.00986
• Code: https://github.com/zsyOAOA/BSRDM
• Tags: Blind SR

Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution

• Paper: https://arxiv.org/abs/2203.09195
• Code: https://github.com/csjliang/LDL
• Tags: Real SR

Dual Adversarial Adaptation for Cross-Device Real-World Image Super-Resolution

• Paper: https://arxiv.org/abs/2205.03524
• Code: GitHub - lonelyhope/DADA
• Tags: Real SR

LAR-SR: A Local Autoregressive Model for Image Super-Resolution

• Paper: CVPR 2022 Open Access Repository

Texture-Based Error Analysis for Image Super-Resolution

• Paper: CVPR 2022 Open Access Repository

Learning to Zoom Inside Camera Imaging Pipeline

• Paper: CVPR 2022 Open Access Repository
• Tags: Raw-to-Raw domain

Task Decoupled Framework for Reference-Based Super-Resolution

• Paper: CVPR 2022 Open Access Repository
• Tags: Reference-Based

GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors

• Paper: https://arxiv.org/abs/2203.07319
• Code: GitHub - hejingwenhejingwen/GCFSR
• Tags: Face SR

A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution

• Paper: https://arxiv.org/abs/2203.09388
• Code: https://github.com/mjq11302010044/TATT
• Tags: Text SR

Learning Graph Regularisation for Guided Super-Resolution

• Paper: https://arxiv.org/abs/2203.14297
• Tags: Guided SR

Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution

• Paper: https://arxiv.org/abs/2203.13963
• Code: https://github.com/XAIMI-Lab/McMRSR
• Tags: MRI SR

Discrete Cosine Transform Network for Guided Depth Map Super-Resolution

• Paper: https://arxiv.org/abs/2104.06977
• Code: https://github.com/Zhaozixiang1228/GDSR-DCTNet
• Tags: Guided Depth Map SR

SphereSR: 360deg Image Super-Resolution With Arbitrary Projection via Continuous Spherical Image Representation

• Paper: CVPR 2022 Open Access Repository

IMDeception: Grouped Information Distilling Super-Resolution Network

• Paper: https://arxiv.org/abs/2204.11463
• Tags: [Workshop], lightweight

A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds

• Paper: https://arxiv.org/abs/2205.04910
• Code: https://github.com/WenlongZhang0517/CloserLookBlindSR
• Tags: [Workshop], Blind SR

Burst/Multi-frame Super Resolution

Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites

• Paper: https://arxiv.org/abs/2205.02031
• Code: GitHub - centreborelli/HDR-DSP-SR: Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites
• Tags: Self-Supervised, multi-exposure

Video Super Resolution

BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment

• Paper: https://arxiv.org/abs/2104.13371
• Code: GitHub - ckkelvinchan/BasicVSR_PlusPlus: Official repository of "BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment"

Learning Trajectory-Aware Transformer for Video Super-Resolution

• Paper: https://arxiv.org/abs/2204.04216
• Code: GitHub - researchmm/TTVSR: [CVPR'22 Oral] TTVSR: Learning Trajectory-Aware Transformer for Video Super-Resolution
• Tags: Transformer

Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modeling

• Paper: https://arxiv.org/abs/2204.07114

Investigating Tradeoffs in Real-World Video Super-Resolution

• Paper: https://arxiv.org/abs/2111.12704
• Code: https://github.com/ckkelvinchan/RealBasicVSR
• Tags: Real-world, RealBaiscVSR

Memory-Augmented Non-Local Attention for Video Super-Resolution

• Paper: CVPR 2022 Open Access Repository

Stable Long-Term Recurrent Video Super-Resolution

• Paper: CVPR 2022 Open Access Repository

Reference-based Video Super-Resolution Using Multi-Camera Video Triplets

• Paper: https://arxiv.org/abs/2203.14537
• Code: https://github.com/codeslake/RefVSR
• Tags: Reference-based VSR

A New Dataset and Transformer for Stereoscopic Video Super-Resolution

• Paper: https://arxiv.org/abs/2204.10039
• Code: https://github.com/H-deep/Trans-SVSR/
• Tags: Stereoscopic Video Super-Resolution

Image Rescaling - 图像缩放

Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence

• Paper: https://arxiv.org/abs/2203.00911

Faithful Extreme Rescaling via Generative Prior Reciprocated Invertible Representations

• Paper: CVPR 2022 Open Access Repository
• Code: https://github.com/cszzx/GRAIN

Denoising - 去噪

Image Denoising

Self-Supervised Image Denoising via Iterative Data Refinement

• Paper: https://arxiv.org/abs/2111.14358
• Code: https://github.com/zhangyi-3/IDR
• Tags: Self-Supervised

Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots

• Paper: https://arxiv.org/abs/2203.06967
• Code: https://github.com/demonsjin/Blind2Unblind
• Tags: Self-Supervised

AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network

• Paper: https://arxiv.org/abs/2203.11799
• Code: https://github.com/wooseoklee4/AP-BSN
• Tags: Self-Supervised

CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image

• Paper: https://arxiv.org/abs/2203.13009
• Code: GitHub - Reyhanehne/CVF-SID_PyTorch
• Tags: Self-Supervised

Noise Distribution Adaptive Self-Supervised Image Denoising Using Tweedie Distribution and Score Matching

• Paper: CVPR 2022 Open Access Repository
• Tags: Self-Supervised

Noise2NoiseFlow: Realistic Camera Noise Modeling without Clean Images

• Paper: https://arxiv.org/abs/2206.01103
• Tags: Noise Modeling, Normalizing Flow

Modeling sRGB Camera Noise with Normalizing Flows

• Paper: https://arxiv.org/abs/2206.00812
• Tags: Noise Modeling, Normalizing Flow

Estimating Fine-Grained Noise Model via Contrastive Learning

• Paper: CVPR 2022 Open Access Repository
• Tags: Noise Modeling, Constrastive Learning

Multiple Degradation and Reconstruction Network for Single Image Denoising via Knowledge Distillation

• Paper: https://arxiv.org/abs/2204.13873
• Tags: [Workshop]

BurstDenoising

NAN: Noise-Aware NeRFs for Burst-Denoising

• Paper: https://arxiv.org/abs/2204.04668
• Tags: NeRFs

Video Denoising

Dancing under the stars: video denoising in starlight

• Paper: https://arxiv.org/abs/2204.04210
• Code: https://github.com/monakhova/starlight_denoising/
• Tags: video denoising in starlight

Deblurring - 去模糊

Image Deblurring

Learning to Deblur using Light Field Generated and Real Defocus Images

• Paper: https://arxiv.org/abs/2204.00367
• Code: https://github.com/lingyanruan/DRBNet
• Tags: Defocus deblurring

Pixel Screening Based Intermediate Correction for Blind Deblurring

• Paper: CVPR 2022 Open Access Repository
• Tags: Blind

Deblurring via Stochastic Refinement

• Paper: CVPR 2022 Open Access Repository

XYDeblur: Divide and Conquer for Single Image Deblurring

• Paper: CVPR 2022 Open Access Repository

Unifying Motion Deblurring and Frame Interpolation with Events

• Paper: https://arxiv.org/abs/2203.12178
• Tags: event-based

E-CIR: Event-Enhanced Continuous Intensity Recovery

• Paper: https://arxiv.org/abs/2203.01935
• Code: https://github.com/chensong1995/E-CIR
• Tags: event-based

Video Deblurring

Multi-Scale Memory-Based Video Deblurring

• Paper: https://arxiv.org/abs/2203.01935
• Code: https://github.com/jibo27/MemDeblur

Deraining - 去雨

Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyond

• Paper: https://arxiv.org/abs/2203.16931
• Code: https://github.com/yuyi-sd/Robust_Rain_Removal

Unpaired Deep Image Deraining Using Dual Contrastive Learning

• Paper: https://arxiv.org/abs/2109.02973
• Tags: Contrastive Learning, Unpaired

Unsupervised Deraining: Where Contrastive Learning Meets Self-similarity

• Paper: https://arxiv.org/abs/2203.11509
• Tags: Contrastive Learning, Unsupervised

Dreaming To Prune Image Deraining Networks

• Paper: CVPR 2022 Open Access Repository

Dehazing - 去雾

Self-augmented Unpaired Image Dehazing via Density and Depth Decomposition

• Paper: CVPR 2022 Open Access Repository
• Code: https://github.com/YaN9-Y/D4
• Tags: Unpaired

Towards Multi-Domain Single Image Dehazing via Test-Time Training

• Paper: CVPR 2022 Open Access Repository

Image Dehazing Transformer With Transmission-Aware 3D Position Embedding

• Paper: CVPR 2022 Open Access Repository

Physically Disentangled Intra- and Inter-Domain Adaptation for Varicolored Haze Removal

• Paper: CVPR 2022 Open Access Repository

Demoireing - 去摩尔纹

Video Demoireing with Relation-Based Temporal Consistency

• Paper: https://arxiv.org/abs/2204.02957
• Code: https://github.com/CVMI-Lab/VideoDemoireing

Frame Interpolation - 插帧

ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolation

• Paper: https://arxiv.org/abs/2111.15483
• Code: https://github.com/danielism97/ST-MFNet

Long-term Video Frame Interpolation via Feature Propagation

• Paper: https://arxiv.org/abs/2203.15427

Many-to-many Splatting for Efficient Video Frame Interpolation

• Paper: https://arxiv.org/abs/2204.03513
• Code: https://github.com/feinanshan/M2M_VFI

Video Frame Interpolation with Transformer

• Paper: https://arxiv.org/abs/2205.07230
• Code: https://github.com/dvlab-research/VFIformer
• Tags: Transformer

Video Frame Interpolation Transformer

• Paper: https://arxiv.org/abs/2111.13817
• Code: https://github.com/zhshi0816/Video-Frame-Interpolation-Transformer
• Tags: Transformer

IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation

• Paper: https://arxiv.org/abs/2205.14620
• Code: GitHub - ltkong218/IFRNet: IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation (CVPR 2022)

TimeReplayer: Unlocking the Potential of Event Cameras for Video Interpolation

• Paper: https://arxiv.org/abs/2203.13859
• Tags: Event Camera

Time Lens++: Event-based Frame Interpolation with Parametric Non-linear Flow and Multi-scale Fusion

• Paper: https://arxiv.org/abs/2203.17191
• Tags: Event-based

Unifying Motion Deblurring and Frame Interpolation with Events

• Paper: https://arxiv.org/abs/2203.12178
• Tags: event-based

Multi-encoder Network for Parameter Reduction of a Kernel-based Interpolation Architecture

• Paper: https://arxiv.org/abs/2205.06723
• Tags: [Workshop]

Spatial-Temporal Video Super-Resolution

RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution

• Paper: https://arxiv.org/abs/2203.14186
• Code: https://github.com/llmpass/RSTT

Spatial-Temporal Space Hand-in-Hand: Spatial-Temporal Video Super-Resolution via Cycle-Projected Mutual Learning

• Paper: https://arxiv.org/abs/2205.05264

VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolution

• Paper: https://arxiv.org/abs/2206.04647
• Code: https://github.com/Picsart-AI-Research/VideoINR-Continuous-Space-Time-Super-Resolution

Image Enhancement - 图像增强

AdaInt: Learning Adaptive Intervals for 3D Lookup Tables on Real-time Image Enhancement

• Paper: https://arxiv.org/abs/2204.13983
• Code: https://github.com/ImCharlesY/AdaInt

Exposure Correction Model to Enhance Image Quality

• Paper: https://arxiv.org/abs/2204.10648
• Code: GitHub - yamand16/ExposureCorrection
• Tags: [Workshop]

Low-Light Image Enhancement

Abandoning the Bayer-Filter to See in the Dark

• Paper: https://arxiv.org/abs/2203.04042
• Code: https://github.com/TCL-AILab/Abandon_Bayer-Filter_See_in_the_Dark

Toward Fast, Flexible, and Robust Low-Light Image Enhancement

• Paper: https://arxiv.org/abs/2204.10137
• Code: GitHub - vis-opt-group/SCI: [CVPR 2022] This is the official code for the paper "Toward Fast, Flexible, and Robust Low-Light Image Enhancement".

Deep Color Consistent Network for Low-Light Image Enhancement

• Paper: CVPR 2022 Open Access Repository

SNR-Aware Low-Light Image Enhancement

• Paper: CVPR 2022 Open Access Repository
• Code: https://github.com/dvlab-research/SNR-Aware-Low-Light-Enhance

URetinex-Net: Retinex-Based Deep Unfolding Network for Low-Light Image Enhancement

• Paper: CVPR 2022 Open Access Repository

Image Harmonization - 图像协调

High-Resolution Image Harmonization via Collaborative Dual Transformationsg

• Paper: https://arxiv.org/abs/2109.06671
• Code: GitHub - bcmi/CDTNet-High-Resolution-Image-Harmonization: [CVPR 2022] We unify pixel-to-pixel transformation and color-to-color transformation in a coherent framework for high-resolution image harmonization. We also release 100 high-resolution real composite images for evaluation.

SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonization

• Paper: https://arxiv.org/abs/2204.13962
• Code: GitHub - YCHang686/SCS-Co-CVPR2022: SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonization (CVPR 2022)

Deep Image-based Illumination Harmonization

• Paper: https://arxiv.org/abs/2108.00150
• Dataset: https://github.com/zhongyunbao/Dataset

Image Completion/Inpainting - 图像修复

Bridging Global Context Interactions for High-Fidelity Image Completion

• Paper: https://arxiv.org/abs/2104.00845
• Code: https://github.com/lyndonzheng/TFill

Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding

• Paper: https://arxiv.org/abs/2203.00867
• Code: GitHub - DQiaole/ZITS_inpainting: Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding (CVPR2022)

MISF: Multi-level Interactive Siamese Filtering for High-Fidelity Image Inpainting

• Paper: https://arxiv.org/abs/2203.06304
• Code: GitHub - tsingqguo/misf

MAT: Mask-Aware Transformer for Large Hole Image Inpainting

• Paper: https://arxiv.org/abs/2203.15270
• Code: GitHub - fenglinglwb/MAT: MAT: Mask-Aware Transformer for Large Hole Image Inpainting

Reduce Information Loss in Transformers for Pluralistic Image Inpainting

• Paper: https://arxiv.org/abs/2205.05076
• Code: GitHub - liuqk3/PUT: Paper 'Reduce Information Loss in Transformers for Pluralistic Image Inpainting' in CVPR2022

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

• Paper: https://arxiv.org/abs/2201.09865
• Code: GitHub - andreas128/RePaint: Official PyTorch Code and Models of "RePaint: Inpainting using Denoising Diffusion Probabilistic Models", CVPR 2022
• Tags: DDPM

Dual-Path Image Inpainting With Auxiliary GAN Inversion

• Paper: CVPR 2022 Open Access Repository

SaiNet: Stereo aware inpainting behind objects with generative networks

• Paper: https://arxiv.org/abs/2205.07014
• Tags: [Workshop]

Video Inpainting

Towards An End-to-End Framework for Flow-Guided Video Inpainting

• Paper: https://arxiv.org/abs/2204.02663
• Code: https://github.com/MCG-NKU/E2FGVI

The DEVIL Is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting

• Paper: CVPR 2022 Open Access Repository
• Code: GitHub - MichiganCOG/devil

DLFormer: Discrete Latent Transformer for Video Inpainting

• Paper: CVPR 2022 Open Access Repository

Inertia-Guided Flow Completion and Style Fusion for Video Inpainting

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Zhang_Inertia-Guided_Flow_Completion_and_Style_Fusion_for_Video_Inpainting_CVPR_2022_paper.htmll

Image Matting - 图像抠图

MatteFormer: Transformer-Based Image Matting via Prior-Tokens

• Paper: https://arxiv.org/abs/2203.15662
• Code: https://github.com/webtoon/matteformer

Human Instance Matting via Mutual Guidance and Multi-Instance Refinement

• Paper: https://arxiv.org/abs/2205.10767
• Code: GitHub - nowsyn/InstMatt: Official repository for Instance Human Matting via Mutual Guidance and Multi-Instance Refinement

Boosting Robustness of Image Matting with Context Assembling and Strong Data Augmentation

• Paper: https://arxiv.org/abs/2201.06889

Shadow Removal - 阴影消除

Bijective Mapping Network for Shadow Removal

• Paper: CVPR 2022 Open Access Repository

Relighting

Face Relighting with Geometrically Consistent Shadows

• Paper: https://arxiv.org/abs/2203.16681
• Code: GitHub - andrewhou1/GeomConsistentFR: Official Code for Face Relighting with Geometrically Consistent Shadows (CVPR 2022)
• Tags: Face Relighting

SIMBAR: Single Image-Based Scene Relighting For Effective Data Augmentation For Automated Driving Vision Tasks

• Paper: https://arxiv.org/abs/2204.00644

Image Stitching - 图像拼接

Deep Rectangling for Image Stitching: A Learning Baseline

• Paper: https://arxiv.org/abs/2203.03831
• Code: https://github.com/nie-lang/DeepRectangling

Automatic Color Image Stitching Using Quaternion Rank-1 Alignment

• Paper: CVPR 2022 Open Access Repository

Geometric Structure Preserving Warp for Natural Image Stitching

• Paper: CVPR 2022 Open Access Repository

Image Compression - 图像压缩

Neural Data-Dependent Transform for Learned Image Compression

• Paper: https://arxiv.org/abs/2203.04963v1

The Devil Is in the Details: Window-based Attention for Image Compression

• Paper: https://arxiv.org/abs/2203.08450
• Code: https://github.com/Googolxx/STF

ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding

• Paper: https://arxiv.org/abs/2203.10886

Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression

• Paper: https://arxiv.org/abs/2203.10897
• Code: GitHub - xiaosu-zhu/McQuic: Repository of CVPR'22 paper "Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression"

DPICT: Deep Progressive Image Compression Using Trit-Planes

• Paper: https://arxiv.org/abs/2112.06334
• Code: https://github.com/jaehanlee-mcl/DPICT

Joint Global and Local Hierarchical Priors for Learned Image Compression

• Paper: CVPR 2022 Open Access Repository

LC-FDNet: Learned Lossless Image Compression With Frequency Decomposition Network

• Paper: CVPR 2022 Open Access Repository

Practical Learned Lossless JPEG Recompression with Multi-Level Cross-Channel Entropy Model in the DCT Domain

• Paper: https://arxiv.org/abs/2203.16357
• Tags: Compress JPEG

SASIC: Stereo Image Compression With Latent Shifts and Stereo Attention

• Paper: CVPR 2022 Open Access Repository
• Tags: Stereo Image Compression

Deep Stereo Image Compression via Bi-Directional Coding

• Paper: CVPR 2022 Open Access Repository
• Tags: Stereo Image Compression

Learning Based Multi-Modality Image and Video Compression

• Paper: CVPR 2022 Open Access Repository

PO-ELIC: Perception-Oriented Efficient Learned Image Coding

• Paper: https://arxiv.org/abs/2205.14501
• Tags: [Workshop]

Video Compression

Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Prediction

• Paper: https://arxiv.org/abs/2206.07460

LSVC: A Learning-Based Stereo Video Compression Framework

• Paper: CVPR 2022 Open Access Repository
• Tags: Stereo Video Compression

Enhancing VVC with Deep Learning based Multi-Frame Post-Processing

• Paper: https://arxiv.org/abs/2205.09458
• Tags: [Workshop]

Image Quality Assessment - 图像质量评价

Personalized Image Aesthetics Assessment with Rich Attributes

• Paper: https://arxiv.org/abs/2203.16754
• Tags: Aesthetics Assessment

Incorporating Semi-Supervised and Positive-Unlabeled Learning for Boosting Full Reference Image Quality Assessment

• Paper: https://arxiv.org/abs/2204.08763
• Code: GitHub - happycaoyue/JSPL
• Tags: FR-IQA

SwinIQA: Learned Swin Distance for Compressed Image Quality Assessment

• Paper: https://arxiv.org/abs/2205.04264
• Tags: [Workshop], compressed IQA

Image Decomposition

PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition

• Paper: CVPR 2022 Open Access Repository
• Code: GitHub - Morpheus3000/PIE-Net: Official model and network release for my CVPR2022 paper.

Deformable Sprites for Unsupervised Video Decomposition

• Paper: https://arxiv.org/abs/2204.07151
• Code: https://github.com/vye16/deformable-sprites

Style Transfer - 风格迁移

CLIPstyler: Image Style Transfer with a Single Text Condition

• Paper: https://arxiv.org/abs/2112.00374
• Code: GitHub - cyclomon/CLIPstyler: Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition" (CVPR 2022)
• Tags: CLIP

Style-ERD: Responsive and Coherent Online Motion Style Transfer

• Paper: https://arxiv.org/abs/2203.02574
• Code: GitHub - tianxintao/Online-Motion-Style-Transfer: Code for the CVPR 2022 Paper - Style-ERD: Responsive and Coherent Online Motion Style Transfer

Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

• Paper: https://arxiv.org/abs/2203.07740
• Code: GitHub - YBZh/EFDM: Official PyTorch codes of CVPR2022 Oral: Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer

• Paper: https://arxiv.org/abs/2203.13248
• Code: https://github.com/williamyang1991/DualStyleGAN

Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation

• Paper: https://arxiv.org/abs/2203.12835
• Code: https://github.com/jcyang98/InST

StyTr2: Image Style Transfer With Transformers

• Paper: CVPR 2022 Open Access Repository

PCA-Based Knowledge Distillation Towards Lightweight and Content-Style Balanced Photorealistic Style Transfer Models

• Paper: https://arxiv.org/abs/2203.13452
• Code: GitHub - chiutaiyin/PCA-Knowledge-Distillation: PCA-based knowledge distillation towards lightweight and content-style balanced photorealistic style transfer models

Image Editing - 图像编辑

High-Fidelity GAN Inversion for Image Attribute Editing

• Paper: https://arxiv.org/abs/2109.06590
• Code: https://github.com/Tengfei-Wang/HFGI

Style Transformer for Image Inversion and Editing

• Paper: https://arxiv.org/abs/2203.07932
• Code: https://github.com/sapphire497/style-transformer

HairCLIP: Design Your Hair by Text and Reference Image

• Paper: https://arxiv.org/abs/2112.05142
• Code: GitHub - wty-ustc/HairCLIP: [CVPR 2022] HairCLIP: Design Your Hair by Text and Reference Image
• Tags: CLIP

HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing

• Paper: https://arxiv.org/abs/2111.15666
• Code: GitHub - yuval-alaluf/hyperstyle: Official Implementation for "HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing" (CVPR 2022) https://arxiv.org/abs/2111.15666

Blended Diffusion for Text-driven Editing of Natural Images

• Paper: https://arxiv.org/abs/2111.14818
• Code: GitHub - omriav/blended-diffusion: Official implementation for "Blended Diffusion for Text-driven Editing of Natural Images" [CVPR 2022]
• Tags: CLIP, Diffusion Model

FlexIT: Towards Flexible Semantic Image Translation

• Paper: https://arxiv.org/abs/2203.04705

SemanticStyleGAN: Learning Compositonal Generative Priors for Controllable Image Synthesis and Editing

• Paper: https://arxiv.org/abs/2112.02236

SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches

• Paper: https://arxiv.org/abs/2111.15078
• Code: https://github.com/zengxianyu/sketchedit

TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing

• Paper: https://arxiv.org/abs/2203.17266
• Code: GitHub - BillyXYB/TransEditor: [CVPR 2022] TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing

HyperInverter: Improving StyleGAN Inversion via Hypernetwork

• Paper: https://arxiv.org/abs/2112.00719
• Code: GitHub - VinAIResearch/HyperInverter: HyperInverter: Improving StyleGAN Inversion via Hypernetwork (CVPR 2022)

Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing

• Paper: https://arxiv.org/abs/2206.08357
• Code: GitHub - adobe-research/sam_inversion: [CVPR 2022] GAN inversion and editing with spatially-adaptive multiple latent layers

Brain-Supervised Image Editing

• Paper: CVPR 2022 Open Access Repository

SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Color Editing

• Paper: CVPR 2022 Open Access Repository

M3L: Language-based Video Editing via Multi-Modal Multi-Level Transformers

• Paper: https://arxiv.org/abs/2104.01122

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

Text to Image Generation with Semantic-Spatial Aware GAN

• Paper: https://arxiv.org/abs/2104.00567
• Code: GitHub - wtliao/text2image: Text to Image Generation with Semantic-Spatial Aware GAN

LAFITE: Towards Language-Free Training for Text-to-Image Generation

• Paper: https://arxiv.org/abs/2111.13792
• Code: https://github.com/drboog/Lafite

DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis

• Paper: https://arxiv.org/abs/2008.05865
• Code: GitHub - tobran/DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis (CVPR2022 oral)

StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis

• Paper: https://arxiv.org/abs/2203.15799
• Code: https://github.com/zhihengli-UR/StyleT2I

DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation

• Paper: https://arxiv.org/abs/2110.02711
• Code: GitHub - gwang-kim/DiffusionCLIP: [CVPR 2022] Official PyTorch Implementation for DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models

Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model

• Paper: https://arxiv.org/abs/2111.13333
• Code: GitHub - zipengxuc/PPE-Pytorch: Pytorch Implementation for CVPR'2022 paper ✨ "Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model"

Sound-Guided Semantic Image Manipulation

• Paper: https://arxiv.org/abs/2112.00007
• Code: https://github.com/kuai-lab/sound-guided-semantic-image-manipulation

ManiTrans: Entity-Level Text-Guided Image Manipulation via Token-wise Semantic Alignment and Generation

• Paper: https://arxiv.org/abs/2204.04428

Text-to-Image Synthesis Based on Object-Guided Joint-Decoding Transformer

• Paper: CVPR 2022 Open Access Repository

Vector Quantized Diffusion Model for Text-to-Image Synthesis

• Paper: https://arxiv.org/abs/2111.14822

AnyFace: Free-style Text-to-Face Synthesis and Manipulation

• Paper: https://arxiv.org/abs/2203.15334

Image-to-Image / Image Guided

Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation

• Paper: https://arxiv.org/abs/2203.12707
• Code: https://github.com/batmanlab/MSPC

A Style-aware Discriminator for Controllable Image Translation

• Paper: https://arxiv.org/abs/2203.15375
• Code: https://github.com/kunheek/style-aware-discriminator

QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation

• Paper: https://arxiv.org/abs/2203.08483
• Code: GitHub - sapphire497/query-selected-attention: Official implementation for "QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation" (CVPR 2022)

InstaFormer: Instance-Aware Image-to-Image Translation with Transformer

• Paper: https://arxiv.org/abs/2203.16248

Marginal Contrastive Correspondence for Guided Image Generation

• Paper: https://arxiv.org/abs/2204.00442
• Code: GitHub - fnzhan/UNITE: Unbalanced Feature Transport for Exemplar-based Image Translation [CVPR 2021] and Marginal Contrastive Correspondence for Guided Image Generation [CVPR 2022]

Unsupervised Image-to-Image Translation with Generative Prior

• Paper: https://arxiv.org/abs/2204.03641
• Code: https://github.com/williamyang1991/GP-UNIT

Exploring Patch-wise Semantic Relation for Contrastive Learning in Image-to-Image Translation Tasks

• Paper: https://arxiv.org/abs/2203.01532
• Code: GitHub - jcy132/Hneg_SRC: Official Pytorch implementation of "Exploring Patch-wise Semantic Relation for Contrastive Learning in Image-to-Image Translation Tasks" (CVPR 2022)

Neural Texture Extraction and Distribution for Controllable Person Image Synthesis

• Paper: https://arxiv.org/abs/2204.06160
• Code: GitHub - RenYurui/Neural-Texture-Extraction-Distribution: The PyTorch implementation for paper "Neural Texture Extraction and Distribution for Controllable Person Image Synthesis" (CVPR2022 Oral)

Unpaired Cartoon Image Synthesis via Gated Cycle Mapping

• Paper: CVPR 2022 Open Access Repository

Day-to-Night Image Synthesis for Training Nighttime Neural ISPs

• Paper: CVPR 2022 Open Access Repository
• Code: GitHub - SamsungLabs/day-to-night

Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint

• Paper: CVPR 2022 Open Access Repository

Wavelet Knowledge Distillation: Towards Efficient Image-to-Image Translation

• Paper: CVPR 2022 Open Access Repository

Self-Supervised Dense Consistency Regularization for Image-to-Image Translation

• Paper: CVPR 2022 Open Access Repository

Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Model

• Paper: https://arxiv.org/abs/2103.15545
• Project Web: "Drop The GAN: In Defense of Patch Nearest Neighbors as as Single Image Generative Models
• Tags: Image manipulation

HairMapper: Removing Hair From Portraits Using GANs

• Paper: CVPR 2022 Open Access Repository

Others for image generation

Attribute Group Editing for Reliable Few-shot Image Generation

• Paper: https://arxiv.org/abs/2203.08422
• Code: https://github.com/UniBester/AGE

Modulated Contrast for Versatile Image Synthesis

• Paper: https://arxiv.org/abs/2203.09333
• Code: GitHub - fnzhan/MoNCE: Modulated Contrast for Versatile Image Synthesis [CVPR 2022]

Interactive Image Synthesis with Panoptic Layout Generation

• Paper: https://arxiv.org/abs/2203.02104

Autoregressive Image Generation using Residual Quantization

• Paper: https://arxiv.org/abs/2203.01941
• Code: GitHub - lucidrains/RQ-Transformer: Implementation of RQ Transformer, proposed in the paper "Autoregressive Image Generation using Residual Quantization"

Dynamic Dual-Output Diffusion Models

• Paper: https://arxiv.org/abs/2203.04304

Exploring Dual-task Correlation for Pose Guided Person Image Generation

• Paper: https://arxiv.org/abs/2203.02910
• Code: GitHub - PangzeCheung/Dual-task-Pose-Transformer-Network: [CVPR 2022] Exploring Dual-task Correlation for Pose Guided Person Image Generation

StyleSwin: Transformer-based GAN for High-resolution Image Generation

• Paper: https://arxiv.org/abs/2112.10762
• Code: GitHub - microsoft/StyleSwin: [CVPR 2022] StyleSwin: Transformer-based GAN for High-resolution Image Generation

Semantic-shape Adaptive Feature Modulation for Semantic Image Synthesis

• Paper: https://arxiv.org/abs/2203.16898
• Code: GitHub - cszy98/SAFM: Semantic-shape Adaptive Feature Modulation for Semantic Image Synthesis (CVPR2022)

Arbitrary-Scale Image Synthesis

• Paper: https://arxiv.org/abs/2204.02273
• Code: https://github.com/vglsd/ScaleParty

InsetGAN for Full-Body Image Generation

• Paper: https://arxiv.org/abs/2203.07293

HairMapper: Removing Hair from Portraits Using GANs

• Paper: http://www.cad.zju.edu.cn/home/jin/cvpr2022/HairMapper.pdf
• Code: https://github.com/oneThousand1000/non-hair-FFHQ

OSSGAN: Open-Set Semi-Supervised Image Generation

• Paper: https://arxiv.org/abs/2204.14249
• Code: https://github.com/raven38/OSSGAN

Retrieval-based Spatially Adaptive Normalization for Semantic Image Synthesis

• Paper: https://arxiv.org/abs/2204.02854
• Code: GitHub - Shi-Yupeng/RESAIL-For-SIS: Retrieval-based Spatially Adaptive Normalization for Semantic Image Synthesis(CVPR2022)

A Closer Look at Few-shot Image Generation

• Paper: https://arxiv.org/abs/2205.03805
• Tags: Few-shot

Ensembling Off-the-shelf Models for GAN Training

• Paper: https://arxiv.org/abs/2112.09130
• Code: https://github.com/nupurkmr9/vision-aided-gan

Few-Shot Font Generation by Learning Fine-Grained Local Styles

• Paper: https://arxiv.org/abs/2205.09965
• Tags: Few-shot

Modeling Image Composition for Complex Scene Generation

• Paper: https://arxiv.org/abs/2206.00923
• Code: GitHub - JohnDreamer/TwFA

Global Context With Discrete Diffusion in Vector Quantised Modelling for Image Generation

• Paper: https://arxiv.org/abs/2112.01799

Self-supervised Correlation Mining Network for Person Image Generation

• Paper: https://arxiv.org/abs/2111.13307

Learning To Memorize Feature Hallucination for One-Shot Image Generation

• Paper: CVPR 2022 Open Access Repository

Local Attention Pyramid for Scene Image Generation

• Paper: CVPR 2022 Open Access Repository

High-Resolution Image Synthesis with Latent Diffusion Models

• Paper: https://arxiv.org/abs/2112.10752
• Code: GitHub - CompVis/latent-diffusion: High-Resolution Image Synthesis with Latent Diffusion Models

Cluster-guided Image Synthesis with Unconditional Models

• Paper: https://arxiv.org/abs/2112.12911

SphericGAN: Semi-Supervised Hyper-Spherical Generative Adversarial Networks for Fine-Grained Image Synthesis

• Paper: CVPR 2022 Open Access Repository

DPGEN: Differentially Private Generative Energy-Guided Network for Natural Image Synthesis

• Paper: CVPR 2022 Open Access Repository

DO-GAN: A Double Oracle Framework for Generative Adversarial Networks

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Aung_DO-GAN_A_Double_Oracle_Framework_for_Generative_Adversarial_Networks_CVPR_2022_paper.html

Improving GAN Equilibrium by Raising Spatial Awareness

• Paper: https://arxiv.org/abs/2112.00718
• Code: https://github.com/genforce/eqgan-sa

**Polymorphic-GAN: Generating Aligned Samples Across Multiple Domains With Learned Morph Maps **

• Paper: CVPR 2022 Open Access Repository

Manifold Learning Benefits GANs

• Paper: https://arxiv.org/abs/2112.12618

Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data

• Paper: https://arxiv.org/abs/2204.04950
• Code: GitHub - FriedRonaldo/Primitives-PS: Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data - Official PyTorch Implementation (CVPR 2022)

On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models

• Paper: https://arxiv.org/abs/2205.03859
• Tags: [Workshop]

Generate and Edit Your Own Character in a Canonical View

• Paper: https://arxiv.org/abs/2205.02974
• Tags: [Workshop]

StyLandGAN: A StyleGAN based Landscape Image Synthesis using Depth-map

• Paper: https://arxiv.org/abs/2205.06611
• Tags: [Workshop]

Overparameterization Improves StyleGAN Inversion

• Paper: https://arxiv.org/abs/2205.06304
• Tags: [Workshop]

Video Generation/Synthesis

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning

• Paper: https://arxiv.org/abs/2203.02573
• Code: https://github.com/snap-research/MMVID

Playable Environments: Video Manipulation in Space and Time

• Paper: https://arxiv.org/abs/2203.01914
• Code: https://github.com/willi-menapace/PlayableEnvironments

StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2

• Paper: https://kaust-cair.s3.amazonaws.com/stylegan-v/stylegan-v-paper.pdf
• Code: https://github.com/universome/stylegan-v

Thin-Plate Spline Motion Model for Image Animation

• Paper: https://arxiv.org/abs/2203.14367
• Code: GitHub - yoyo-nb/Thin-Plate-Spline-Motion-Model: [CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.

Make It Move: Controllable Image-to-Video Generation with Text Descriptions

• Paper: https://arxiv.org/abs/2112.02815
• Code: GitHub - Youncy-Hu/MAGE: Make It Move: Controllable Image-to-Video Generation with Text Descriptions

Diverse Video Generation from a Single Video

• Paper: https://arxiv.org/abs/2205.05725
• Tags: [Workshop]

Others

GAN-Supervised Dense Visual Alignment

• Paper: https://arxiv.org/abs/2112.05143
• Code: https://github.com/wpeebles/gangealing

ClothFormer:Taming Video Virtual Try-on in All Module

• Paper: https://arxiv.org/abs/2204.12151
• Tags: Video Virtual Try-on

Iterative Deep Homography Estimation

• Paper: https://arxiv.org/abs/2203.15982
• Code: GitHub - imdumpl78/IHN: This is the open source implementation of the CVPR2022 paper "Iterative Deep Homography Estimation"

Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization

• Paper: https://openaccess.thecvf.com/content/CVPR2022/papers/Li_Style-Structure_Disentangled_Features_and_Normalizing_Flows_for_Diverse_Icon_Colorization_CVPR_2022_paper.pdf
• Code: GitHub - djosix/IconFlow: Code for "Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization", CVPR 2022.

Unsupervised Homography Estimation with Coplanarity-Aware GAN

• Paper: https://arxiv.org/abs/2205.03821
• Code: GitHub - megvii-research/HomoGAN: This is the official implementation of HomoGAN, CVPR2022

Diverse Image Outpainting via GAN Inversion

• Paper: https://arxiv.org/abs/2104.00675
• Code: GitHub - yccyenchicheng/InOut: Diverse Image Outpainting via GAN Inversion

On Aliased Resizing and Surprising Subtleties in GAN Evaluation

• Paper: https://arxiv.org/abs/2104.11222
• Code: GitHub - GaParmar/clean-fid: PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]

Patch-wise Contrastive Style Learning for Instagram Filter Removal

• Paper: https://arxiv.org/abs/2204.07486
• Code: GitHub - birdortyedi/cifr-pytorch
• Tags: [Workshop]

NTIRE2022

New Trends in Image Restoration and Enhancement workshop and challenges on image and video processing.

Spectral Reconstruction from RGB

MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction

• Paper: https://arxiv.org/abs/2204.07908
• Code: GitHub - caiyuanhao1998/MST-plus-plus: "MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction" (CVPRW 2022) & (Winner of NTIRE 2022 Spectral Recovery Challenge) and a toolbox for spectral reconstruction
• Tags: 1st place

Perceptual Image Quality Assessment: Track 1 Full-Reference / Track 2 No-Reference

MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

• Paper: https://arxiv.org/abs/2204.08958
• Code: GitHub - IIGROUP/MANIQA: [CVPRW 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
• Tags: 1st place for track2

Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network

• Paper: https://arxiv.org/abs/2204.10485
• Code: GitHub - IIGROUP/AHIQ: [CVPRW 2022] Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network
• Tags: 1st place for track1

MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusion

• Paper: https://arxiv.org/abs/2205.10101
• Tags: 2nd place in track2

Conformer and Blind Noisy Students for Improved Image Quality Assessment

• Paper: https://arxiv.org/abs/2204.12819

Inpainting: Track 1 Unsupervised / Track 2 Semantic

GLaMa: Joint Spatial and Frequency Loss for General Image Inpainting

• Paper: https://arxiv.org/abs/2205.07162
• Tags: ranked first in terms of PSNR, LPIPS and SSIM in the track1

Efficient Super-Resolution

• Report: https://arxiv.org/abs/2205.05675

ShuffleMixer: An Efficient ConvNet for Image Super-Resolution

• Paper: https://arxiv.org/abs/2205.15175
• Code: https://github.com/sunny2109/MobileSR-NTIRE2022
• Tags: Winner of the model complexity track

Edge-enhanced Feature Distillation Network for Efficient Super-Resolution

• Paper: https://arxiv.org/abs/2204.08759
• Code: https://github.com/icandle/EFDN

Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution

• Paper: https://arxiv.org/abs/2204.08759
• Code: GitHub - NJU-Jet/FMEN: Lowest memory consumption and second shortest runtime in NTIRE 2022 challenge on Efficient Super-Resolution
• Tags: Lowest memory consumption and second shortest runtime

Blueprint Separable Residual Network for Efficient Image Super-Resolution

• Paper: https://arxiv.org/abs/2205.05996
• Code: GitHub - xiaom233/BSRN: Blueprint Separable Residual Network for Efficient Image Super-Resolution
• Tags: 1st place in model complexity track

Night Photography Rendering

Rendering Nighttime Image Via Cascaded Color and Brightness Compensation

• Paper: https://arxiv.org/abs/2204.08970
• Code: GitHub - NJUVISION/CBUnet: Official code of the "Rendering Nighttime Image Via Cascaded Color and Brightness Compensation"
• Tags: 2nd place

Super-Resolution and Quality Enhancement of Compressed Video: Track1 (Quality enhancement) / Track2 (Quality enhancement and x2 SR) / Track3 (Quality enhancement and x4 SR)

• Report: https://arxiv.org/abs/2204.09314
• Homepage: GitHub - RenYang-home/NTIRE22_VEnh_SR

Progressive Training of A Two-Stage Framework for Video Restoration

• Paper: https://arxiv.org/abs/2204.09924
• Code: GitHub - ryanxingql/winner-ntire22-vqe: Our method and experience of wining the NTIRE22 challenge on video quality enhancement
• Tags: 1st place in track1 and track2, 2nd place in track3

High Dynamic Range (HDR): Track 1 Low-complexity (fidelity constrain) / Track 2 Fidelity (low-complexity constrain)

• Report: https://arxiv.org/abs/2205.12633

Efficient Progressive High Dynamic Range Image Restoration via Attention and Alignment Network

• Paper: https://arxiv.org/abs/2204.09213
• Tags: 2nd palce of both two tracks

Stereo Super-Resolution

• Report: https://arxiv.org/abs/2204.09197

Parallel Interactive Transformer

• Code: GitHub - chaineypung/CVPR-NTIRE2022-Parallel-Interactive-Transformer: This is the source code of the 7th place solution for stereo image super resolution task in 2022 CVPR NTIRE challenge.
• Tags: 7st place

Burst Super-Resolution: Track 2 Real

BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment

• Code: https://github.com/Algolzw/BSRT
• Tags: 1st place

ECCV2022-Low-Level-Vision

Image Restoration - 图像恢复

Simple Baselines for Image Restoration

• Paper: https://arxiv.org/abs/2204.04676
• Code: https://github.com/megvii-research/NAFNet

D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration

• Paper: https://arxiv.org/abs/2207.03294
• Code: https://github.com/zhaoyuzhi/D2HNet

Seeing Far in the Dark with Patterned Flash

• Paper: https://arxiv.org/abs/2207.12570
• Code: https://github.com/zhsun0357/Seeing-Far-in-the-Dark-with-Patterned-Flash

BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks

• Paper: https://arxiv.org/abs/2207.06873
• Code: https://github.com/ExplainableML/BayesCap

Improving Image Restoration by Revisiting Global Information Aggregation

• Paper: https://arxiv.org/abs/2112.04491
• Code: https://github.com/megvii-research/TLC

Fast Two-step Blind Optical Aberration Correction

• Paper: https://arxiv.org/abs/2208.00950
• Code: https://github.com/teboli/fast_two_stage_psf_correction
• Tags: Optical Aberration Correction

VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder

• Paper: https://arxiv.org/abs/2205.06803
• Code: https://github.com/TencentARC/VQFR
• Tags: Blind Face Restoration

RAWtoBit: A Fully End-to-end Camera ISP Network

• Paper: https://arxiv.org/abs/2208.07639
• Tags: ISP and Image Compression

Transform your Smartphone into a DSLR Camera: Learning the ISP in the Wild

• Paper: https://arxiv.org/abs/2203.10636
• Code: https://github.com/4rdhendu/TransformPhone2DSLR
• Tags: ISP

Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model

• Paper: https://arxiv.org/abs/2207.10040
• Code: https://github.com/VITA-Group/TurbNet
• Tags: Atmospheric Turbulence Mitigation, Transformer

Modeling Mask Uncertainty in Hyperspectral Image Reconstruction

• Paper: https://arxiv.org/abs/2112.15362
• Code: https://github.com/Jiamian-Wang/mask_uncertainty_spectral_SCI
• Tags: Hyperspectral Image Reconstruction

TAPE: Task-Agnostic Prior Embedding for Image Restoration

• Paper: ECVA | European Computer Vision Association

DRCNet: Dynamic Image Restoration Contrastive Network

• Paper: ECVA | European Computer Vision Association

ART-SS: An Adaptive Rejection Technique for Semi-Supervised Restoration for Adverse Weather-Affected Images

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/rajeevyasarla/ART-SS
• Tags: Adverse Weather

Spectrum-Aware and Transferable Architecture Search for Hyperspectral Image Restoration

• Paper: ECVA | European Computer Vision Association
• Tags: Hyperspectral Image Restoration

Seeing through a Black Box: Toward High-Quality Terahertz Imaging via Subspace-and-Attention Guided Restoration

• Paper: ECVA | European Computer Vision Association
• Tags: Terahertz Imaging

JPEG Artifacts Removal via Contrastive Representation Learning

• Paper: ECVA | European Computer Vision Association
• Tags: JPEG Artifacts Removal

Zero-Shot Learning for Reflection Removal of Single 360-Degree Image

• Paper: ECVA | European Computer Vision Association
• Tags: Reflection Removal

Overexposure Mask Fusion: Generalizable Reverse ISP Multi-Step Refinement

• Paper: https://arxiv.org/abs/2210.11511
• Code: https://github.com/SenseBrainTech/overexposure-mask-reverse-ISP
• Tagss: [Workshop], Reversed ISP

Video Restoration

Video Restoration Framework and Its Meta-Adaptations to Data-Poor Conditions

• Paper: ECVA | European Computer Vision Association

Super Resolution - 超分辨率

Image Super Resolution

ARM: Any-Time Super-Resolution Method

• Paper: https://arxiv.org/abs/2203.10812
• Code: https://github.com/chenbong/ARM-Net

Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks

• Paper: https://arxiv.org/abs/2203.03844
• Code: https://github.com/zysxmu/DDTB

CADyQ : Contents-Aware Dynamic Quantization for Image Super Resolution

• Paper: https://arxiv.org/abs/2207.10345
• Code: https://github.com/Cheeun/CADyQ

Image Super-Resolution with Deep Dictionary

• Paper: https://arxiv.org/abs/2207.09228
• Code: https://github.com/shuntama/srdd

Perception-Distortion Balanced ADMM Optimization for Single-Image Super-Resolution

• Paper: https://arxiv.org/abs/2208.03324
• Code: https://github.com/Yuehan717/PDASR

Adaptive Patch Exiting for Scalable Single Image Super-Resolution

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/littlepure2333/APE

Learning Series-Parallel Lookup Tables for Efficient Image Super-Resolution

• Paper: https://arxiv.org/abs/2207.12987
• Code: https://github.com/zhjy2016/SPLUT
• Tags: Efficient

MuLUT: Cooperating Mulitple Look-Up Tables for Efficient Image Super-Resolution

• Paper: https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136780234.pdf
• Code: https://github.com/ddlee-cn/MuLUT
• Tags: Efficient

Efficient Long-Range Attention Network for Image Super-resolution

• Paper: https://arxiv.org/abs/2203.06697
• Code: https://github.com/xindongzhang/ELAN

Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution

• Paper: https://arxiv.org/abs/2207.12577
• Code: https://github.com/wuyushuwys/compiler-aware-nas-sr

Restore Globally, Refine Locally: A Mask-Guided Scheme to Accelerate Super-Resolution Networks

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/huxiaotaostasy/MGA-scheme

Learning Mutual Modulation for Self-Supervised Cross-Modal Super-Resolution

• Paper: https://arxiv.org/abs/2207.09156
• Code: https://github.com/palmdong/MMSR
• Tags: Self-Supervised

Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed Observations

• Paper: https://arxiv.org/abs/2203.01325
• Code: https://github.com/cszhilu1998/SelfDZSR
• Tags: Self-Supervised, Reference-based

Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution

• Paper: http://www4.comp.polyu.edu.hk/~cslzhang/paper/ECCV2022_DASR.pdf
• Code: https://github.com/csjliang/DASR
• Tags: Real-World

D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution

• Paper: https://arxiv.org/abs/2103.14373
• Code: https://github.com/megvii-research/D2C-SR
• Tag: Real-World

MM-RealSR: Metric Learning based Interactive Modulation for Real-World Super-Resolution

• Paper: https://arxiv.org/abs/2205.05065
• Code: https://github.com/TencentARC/MM-RealSR
• Tag: Real-World

KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution

• Paper: https://arxiv.org/abs/2209.10305
• Code: https://github.com/jiahong-fu/KXNet
• Tags: Blind

From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution

• Paper: https://arxiv.org/abs/2210.00752
• Code: https://github.com/csxmli2016/ReDegNet
• Tags: Blind

Unfolded Deep Kernel Estimation for Blind Image Super-Resolution

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/natezhenghy/UDKE
• Tags: Blind

Uncertainty Learning in Kernel Estimation for Multi-stage Blind Image Super-Resolution

• Paper: ECVA | European Computer Vision Association
• Tags: Blind

Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images

• Paper: https://arxiv.org/abs/2210.04198
• Code: https://github.com/HaomingCai/SRPO
• Tags: Rasterized Images

Reference-based Image Super-Resolution with Deformable Attention Transformer

• Paper: https://arxiv.org/abs/2207.11938
• Code: https://github.com/caojiezhang/DATSR
• Tags: Reference-based, Transformer

RRSR:Reciprocal Reference-Based Image Super-Resolution with Progressive Feature Alignment and Selection

• Paper: ECVA | European Computer Vision Association
• Tags: Reference-based

Boosting Event Stream Super-Resolution with a Recurrent Neural Network

• Paper: ECVA | European Computer Vision Association
• Tags: Event

HST: Hierarchical Swin Transformer for Compressed Image Super-resolution

• Paper: https://arxiv.org/abs/2208.09885
• Tags: [Workshop-AIM2022]

Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration

• Paper: https://arxiv.org/abs/2209.11345
• Code: https://github.com/mv-lab/swin2sr
• Tags: [Workshop-AIM2022]

Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution

• Paper: https://arxiv.org/abs/2208.11609
• Code: https://github.com/Algolzw/NCNet
• Tags: [Workshop-AIM2022]

Video Super Resolution

Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution

• Paper: https://arxiv.org/abs/2208.03012
• Code: https://github.com/researchmm/FTVSR
• Tags: Compressed Video SR

A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolution

• Paper: ECVA | European Computer Vision Association
• Tags: Compressed Video SR

Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark Dataset

• Paper: https://arxiv.org/abs/2209.12475
• Code: https://github.com/zmzhang1998/Real-RawVSR

Denoising - 去噪

Image Denoising

Deep Semantic Statistics Matching (D2SM) Denoising Network

• Paper: https://arxiv.org/abs/2207.09302
• Code: https://github.com/MKFMIKU/d2sm

Fast and High Quality Image Denoising via Malleable Convolution

• Paper: ECVA | European Computer Vision Association

Video Denoising

Unidirectional Video Denoising by Mimicking Backward Recurrent Modules with Look-ahead Forward Ones

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/nagejacob/FloRNN

TempFormer: Temporally Consistent Transformer for Video Denoising

• Paper: ECVA | European Computer Vision Association
• Tags: Transformer

Deblurring - 去模糊

Image Deblurring

Learning Degradation Representations for Image Deblurring

• Paper: https://arxiv.org/abs/2208.05244
• Code: https://github.com/dasongli1/Learning_degradation

Stripformer: Strip Transformer for Fast Image Deblurring

• Paper: ECVA | European Computer Vision Association
• Tags: Transformer

Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance

• Paper: https://arxiv.org/abs/2207.10123
• Code: https://github.com/zzh-tech/Animation-from-Blur
• Tags: recovering detailed motion from a single motion-blurred image

United Defocus Blur Detection and Deblurring via Adversarial Promoting Learning

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/wdzhao123/APL
• Tags: Defocus Blur

Realistic Blur Synthesis for Learning Image Deblurring

• Paper: ECVA | European Computer Vision Association
• Tags: Blur Synthesis

Event-based Fusion for Motion Deblurring with Cross-modal Attention

• Paper:https://arxiv.org/abs/2112.00167
• Code: https://github.com/AHupuJR/EFNet
• Tags: Event-based

Event-Guided Deblurring of Unknown Exposure Time Videos

• Paper: ECVA | European Computer Vision Association
• Tags: Event-based

Video Deblurring

Spatio-Temporal Deformable Attention Network for Video Deblurring

• Paper: https://arxiv.org/abs/2207.10852
• Code: https://github.com/huicongzhang/STDAN

Efficient Video Deblurring Guided by Motion Magnitude

• Paper: https://arxiv.org/abs/2207.13374
• Code: https://github.com/sollynoay/MMP-RNN

ERDN: Equivalent Receptive Field Deformable Network for Video Deblurring

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/TencentCloud/ERDN

DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting

• Paper: https://arxiv.org/abs/2111.09985
• Code: https://github.com/JihyongOh/DeMFI
• Tags: Joint Deblurring and Frame Interpolation

Towards Real-World Video Deblurring by Exploring Blur Formation Process

• Paper: https://arxiv.org/abs/2208.13184
• Tags: [Workshop-AIM2022]

Image Decomposition

Blind Image Decomposition

• Paper: https://arxiv.org/abs/2108.11364
• Code: https://github.com/JunlinHan/BID

Deraining - 去雨

Not Just Streaks: Towards Ground Truth for Single Image Deraining

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/UCLA-VMG/GT-RAIN

Rethinking Video Rain Streak Removal: A New Synthesis Model and a Deraining Network with Video Rain Prior

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/wangshauitj/RDD-Net

Dehazing - 去雾

Frequency and Spatial Dual Guidance for Image Dehazing

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/yuhuUSTC/FSDGN

Perceiving and Modeling Density for Image Dehazing

• Paper: https://arxiv.org/abs/2111.09733
• Code: https://github.com/Owen718/ECCV22-Perceiving-and-Modeling-Density-for-Image-Dehazing

Boosting Supervised Dehazing Methods via Bi-Level Patch Reweighting

• Paper: ECVA | European Computer Vision Association

Unpaired Deep Image Dehazing Using Contrastive Disentanglement Learning

• Paper: ECVA | European Computer Vision Association

Demoireing - 去摩尔纹

Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing

• Paper: https://arxiv.org/abs/2207.09935
• Code: https://github.com/XinYu-Andy/uhdm-page

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

Exposure-Aware Dynamic Weighted Learning for Single-Shot HDR Imaging

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/viengiaan/EDWL

Ghost-free High Dynamic Range Imaging with Context-aware Transformer

• Paper: https://arxiv.org/abs/2208.05114
• Code: https://github.com/megvii-research/HDR-Transformer

Selective TransHDR: Transformer-Based Selective HDR Imaging Using Ghost Region Mask

• Paper: ECVA | European Computer Vision Association

HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields

• Paper: https://arxiv.org/abs/2208.06787
• Code: https://github.com/postech-ami/HDR-Plenoxels

Towards Real-World HDRTV Reconstruction: A Data Synthesis-Based Approach

• Paper: ECVA | European Computer Vision Association

Image Fusion

FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion

• Paper: https://arxiv.org/abs/2209.11277

Recurrent Correction Network for Fast and Efficient Multi-modality Image Fusion

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/MisakiCoca/ReCoNet

Neural Image Representations for Multi-Image Fusion and Layer Separation

• Paper: https://arxiv.org/abs/2108.01199
• Code: Seonghyeon Nam | Neural Image Representations for Multi-Image Fusion and Layer Separation

Fusion from Decomposition: A Self-Supervised Decomposition Approach for Image Fusion

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/erfect2020/DecompositionForFusion

Frame Interpolation - 插帧

Real-Time Intermediate Flow Estimation for Video Frame Interpolation

• Paper: https://arxiv.org/abs/2011.06294
• Code: https://github.com/hzwer/ECCV2022-RIFE

FILM: Frame Interpolation for Large Motion

• Paper: https://arxiv.org/abs/2202.04901
• Code: https://github.com/google-research/frame-interpolation

Video Interpolation by Event-driven Anisotropic Adjustment of Optical Flow

• Paper: https://arxiv.org/abs/2208.09127

Learning Cross-Video Neural Representations for High-Quality Frame Interpolation

• Paper: ECVA | European Computer Vision Association

Deep Bayesian Video Frame Interpolation

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/Oceanlib/DBVI

A Perceptual Quality Metric for Video Frame Interpolation

• Paper: https://arxiv.org/abs/2210.01879
• Code: https://github.com/hqqxyy/VFIPS

DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting

• Paper: https://arxiv.org/abs/2111.09985
• Code: https://github.com/JihyongOh/DeMFI
• Tags: Joint Deblurring and Frame Interpolation

Spatial-Temporal Video Super-Resolution

Towards Interpretable Video Super-Resolution via Alternating Optimization

• Paper: https://arxiv.org/abs/2207.10765
• Code: https://github.com/caojiezhang/DAVSR

Image Enhancement - 图像增强

Local Color Distributions Prior for Image Enhancement

• Paper: https://www.cs.cityu.edu.hk/~rynson/papers/eccv22b.pdf
• Code: https://github.com/hywang99/LCDPNet

SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancement

• Paper: https://arxiv.org/abs/2207.08351

Neural Color Operators for Sequential Image Retouching

• Paper: https://arxiv.org/abs/2207.08080
• Code: https://github.com/amberwangyili/neurop

Deep Fourier-Based Exposure Correction Network with Spatial-Frequency Interaction

• Paper: ECVA | European Computer Vision Association
• Tags: Exposure Correction

Uncertainty Inspired Underwater Image Enhancement

• Paper: ECVA | European Computer Vision Association
• Tags: Underwater Image Enhancement

NEST: Neural Event Stack for Event-Based Image Enhancement

• Paper: ECVA | European Computer Vision Association
• Tags: Event-Based

Low-Light Image Enhancement

LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

• Paper: https://arxiv.org/abs/2202.03373
• Code: https://github.com/sczhou/LEDNet

Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression

• Paper: https://arxiv.org/abs/2207.10564
• Code: https://github.com/jinyeying/night-enhancement

Image Harmonization - 图像协调

Harmonizer: Learning to Perform White-Box Image and Video Harmonization

• Paper: https://arxiv.org/abs/2207.01322
• Code: https://github.com/ZHKKKe/Harmonizer

DCCF: Deep Comprehensible Color Filter Learning Framework for High-Resolution Image Harmonization

• Paper: https://arxiv.org/abs/2207.04788
• Code: https://github.com/rockeyben/DCCF

Semantic-Guided Multi-Mask Image Harmonization

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/XuqianRen/Semantic-guided-Multi-mask-Image-Harmonization

Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization

• Paper: https://arxiv.org/abs/2109.05750
• Code: https://github.com/stefanLeong/S2CRNet

Image Completion/Inpainting - 图像修复

Learning Prior Feature and Attention Enhanced Image Inpainting

• Paper: https://arxiv.org/abs/2208.01837
• Code: https://github.com/ewrfcas/MAE-FAR

Perceptual Artifacts Localization for Inpainting

• Paper: https://arxiv.org/abs/2208.03357
• Code: https://github.com/owenzlz/PAL4Inpaint

High-Fidelity Image Inpainting with GAN Inversion

• Paper: https://arxiv.org/abs/2208.11850

Unbiased Multi-Modality Guidance for Image Inpainting

• Paper: https://arxiv.org/abs/2208.11844

Image Inpainting with Cascaded Modulation GAN and Object-Aware Training

• Paper: https://arxiv.org/abs/2203.11947
• Code: https://github.com/htzheng/CM-GAN-Inpainting

Inpainting at Modern Camera Resolution by Guided PatchMatch with Auto-Curation

• Paper: ECVA | European Computer Vision Association

Diverse Image Inpainting with Normalizing Flow

• Paper: ECVA | European Computer Vision Association

Hourglass Attention Network for Image Inpainting

• Paper: ECVA | European Computer Vision Association

Perceptual Artifacts Localization for Inpainting

• Paper: ECVA | European Computer Vision Association

Don't Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context

• Paper: https://arxiv.org/abs/2207.10273
• Code: https://github.com/lcy0604/CTRNet
• Tags: Text Removal

The Surprisingly Straightforward Scene Text Removal Method with Gated Attention and Region of Interest Generation: A Comprehensive Prominent Model Analysis

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/naver/garnet
• Tags: Text Removal

Video Inpainting

Error Compensation Framework for Flow-Guided Video Inpainting

• Paper: https://arxiv.org/abs/2207.10391

Flow-Guided Transformer for Video Inpainting

• Paper: https://arxiv.org/abs/2208.06768
• Code: https://github.com/hitachinsk/FGT

Image Colorization - 图像上色

Eliminating Gradient Conflict in Reference-based Line-art Colorization

• Paper: https://arxiv.org/abs/2207.06095
• Code: https://github.com/kunkun0w0/SGA

Bridging the Domain Gap towards Generalization in Automatic Colorization

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/Lhyejin/DG-Colorization

CT2: Colorization Transformer via Color Tokens

• Paper: https://ci.idm.pku.edu.cn/Weng_ECCV22b.pdf
• Code: https://github.com/shuchenweng/CT2

PalGAN: Image Colorization with Palette Generative Adversarial Networks

• Paper: https://arxiv.org/abs/2210.11204
• Code: https://github.com/shepnerd/PalGAN

BigColor: Colorization using a Generative Color Prior for Natural Images

• Paper: https://kimgeonung.github.io/assets/bigcolor/bigcolor_main.pdf
• Code: https://github.com/KIMGEONUNG/BigColor

Semantic-Sparse Colorization Network for Deep Exemplar-Based Colorization

• Paper: ECVA | European Computer Vision Association

ColorFormer: Image Colorization via Color Memory Assisted Hybrid-Attention Transformer

• Paper: ECVA | European Computer Vision Association

L-CoDer: Language-Based Colorization with Color-Object Decoupling Transformer

• Paper: ECVA | European Computer Vision Association

Colorization for In Situ Marine Plankton Images

• Paper: ECVA | European Computer Vision Association

Image Matting - 图像抠图

TransMatting: Enhancing Transparent Objects Matting with Transformers

• Paper: https://arxiv.org/abs/2208.03007
• Code: https://github.com/AceCHQ/TransMatting

One-Trimap Video Matting

• Paper: https://arxiv.org/abs/2207.13353
• Code: https://github.com/Hongje/OTVM

Shadow Removal - 阴影消除

Style-Guided Shadow Removal

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/jinwan1994/SG-ShadowNet

Image Compression - 图像压缩

Optimizing Image Compression via Joint Learning with Denoising

• Paper: https://arxiv.org/abs/2207.10869
• Code: https://github.com/felixcheng97/DenoiseCompression

Implicit Neural Representations for Image Compression

• Paper: https://arxiv.org/abs/2112.04267
• Code：https://github.com/YannickStruempler/inr_based_compression

Expanded Adaptive Scaling Normalization for End to End Image Compression

• Paper: https://arxiv.org/abs/2208.03049

Content-Oriented Learned Image Compression

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/lmijydyb/COLIC

Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression

• Paper: ECVA | European Computer Vision Association

Content Adaptive Latents and Decoder for Neural Image Compression

• Paper: ECVA | European Computer Vision Association

Video Compression

AlphaVC: High-Performance and Efficient Learned Video Compression

• Paper: https://arxiv.org/abs/2207.14678

CANF-VC: Conditional Augmented Normalizing Flows for Video Compression

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/NYCU-MAPL/CANF-VC

Neural Video Compression Using GANs for Detail Synthesis and Propagation

• Paper: ECVA | European Computer Vision Association

Image Quality Assessment - 图像质量评价

FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling

• Paper: https://arxiv.org/abs/2207.02595
• Code: https://github.com/TimothyHTimothy/FAST-VQA

Shift-tolerant Perceptual Similarity Metric

• Paper: https://arxiv.org/abs/2207.13686
• Code: GitHub - abhijay9/ShiftTolerant-LPIPS

Telepresence Video Quality Assessment

• Paper: https://arxiv.org/abs/2207.09956

A Perceptual Quality Metric for Video Frame Interpolation

• Paper: https://arxiv.org/abs/2210.01879
• Code: https://github.com/hqqxyy/VFIPS

Relighting/Delighting

Deep Portrait Delighting

• Paper: ECVA | European Computer Vision Association

Geometry-Aware Single-Image Full-Body Human Relighting

• Paper: ECVA | European Computer Vision Association

NeRF for Outdoor Scene Relighting

• Paper: ECVA | European Computer Vision Association

Physically-Based Editing of Indoor Scene Lighting from a Single Image

• Paper: ECVA | European Computer Vision Association

Style Transfer - 风格迁移

CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer

• Paper: https://arxiv.org/abs/2207.04808
• Code: https://github.com/JarrentWu1031/CCPL

Image-Based CLIP-Guided Essence Transfer

• Paper: https://arxiv.org/abs/2110.12427
• Code: https://github.com/hila-chefer/TargetCLIP

Learning Graph Neural Networks for Image Style Transfer

• Paper: https://arxiv.org/abs/2207.11681

WISE: Whitebox Image Stylization by Example-based Learning

• Paper: https://arxiv.org/abs/2207.14606
• Code: https://github.com/winfried-loetzsch/wise

Language-Driven Artistic Style Transfer

• Paper: ECVA | European Computer Vision Association

MoDA: Map Style Transfer for Self-Supervised Domain Adaptation of Embodied Agents

• Paper: ECVA | European Computer Vision Association

JoJoGAN: One Shot Face Stylization

• Paper: https://arxiv.org/abs/2112.11641
• Code: https://github.com/mchong6/JoJoGAN

EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer

• Paper: https://arxiv.org/abs/2207.09840
• Code: https://github.com/Chenyu-Yang-2000/EleGANt
• Tags: Makeup Transfer

RamGAN: Region Attentive Morphing GAN for Region-Level Makeup Transfer

• Paper: ECVA | European Computer Vision Association
• Tags: Makeup Transfer

Image Editing - 图像编辑

Context-Consistent Semantic Image Editing with Style-Preserved Modulation

• Paper: https://arxiv.org/abs/2207.06252
• Code: https://github.com/WuyangLuo/SPMPGAN

GAN with Multivariate Disentangling for Controllable Hair Editing

• Paper: https://raw.githubusercontent.com/XuyangGuo/xuyangguo.github.io/main/database/CtrlHair/CtrlHair.pdf
• Code: https://github.com/XuyangGuo/CtrlHair

Paint2Pix: Interactive Painting based Progressive Image Synthesis and Editing

• Paper: https://arxiv.org/abs/2208.08092
• Code: https://github.com/1jsingh/paint2pix

High-fidelity GAN Inversion with Padding Space

• Paper: https://arxiv.org/abs/2203.11105
• Code: https://github.com/EzioBy/padinv

Text2LIVE: Text-Driven Layered Image and Video Editing

• Paper: https://arxiv.org/abs/2204.02491
• Code: https://github.com/omerbt/Text2LIVE

IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion

• Paper: https://arxiv.org/abs/2209.10811

Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment

• Paper: https://arxiv.org/abs/2208.07765
• Code: https://github.com/Taeu/Style-Your-Hair

HairNet: Hairstyle Transfer with Pose Changes

• Paper: ECVA | European Computer Vision Association

End-to-End Visual Editing with a Generatively Pre-trained Artist

• Paper: ECVA | European Computer Vision Association

The Anatomy of Video Editing: A Dataset and Benchmark Suite for AI-Assisted Video Editing

• Paper: ECVA | European Computer Vision Association

Scraping Textures from Natural Images for Synthesis and Editing

• Paper: ECVA | European Computer Vision Association

VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance

• Paper: ECVA | European Computer Vision Association

Editing Out-of-Domain GAN Inversion via Differential Activations

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/HaoruiSong622/Editing-Out-of-Domain

ChunkyGAN: Real Image Inversion via Segments

• Paper: ECVA | European Computer Vision Association

FairStyle: Debiasing StyleGAN2 with Style Channel Manipulations

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/catlab-team/fairstyle

A Style-Based GAN Encoder for High Fidelity Reconstruction of Images and Videos

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/InterDigitalInc/FeatureStyleEncoder

Rayleigh EigenDirections (REDs): Nonlinear GAN latent space traversals for multidimensional features

• Paper: ECVA | European Computer Vision Association

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

TIPS: Text-Induced Pose Synthesis

• Paper: https://arxiv.org/abs/2207.11718
• Code: https://github.com/prasunroy/tips

TISE: A Toolbox for Text-to-Image Synthesis Evaluation

• Paper: https://arxiv.org/abs/2112.01398
• Code: https://github.com/VinAIResearch/tise-toolbox

Learning Visual Styles from Audio-Visual Associations

• Paper: https://arxiv.org/abs/2205.05072
• Code: https://github.com/Tinglok/avstyle

Multimodal Conditional Image Synthesis with Product-of-Experts GANs

• Paper: ECVA | European Computer Vision Association
• Project: https://deepimagination.cc/PoE-GAN/

NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion

• Paper: ECVA | European Computer Vision Association

Make-a-Scene: Scene-Based Text-to-Image Generation with Human Priors

• Paper: ECVA | European Computer Vision Association

Trace Controlled Text to Image Generation

• Paper: ECVA | European Computer Vision Association

Audio-Driven Stylized Gesture Generation with Flow-Based Model

• Paper: ECVA | European Computer Vision Association

No Token Left Behind: Explainability-Aided Image Classification and Generation

• Paper: ECVA | European Computer Vision Association

Image-to-Image / Image Guided

End-to-end Graph-constrained Vectorized Floorplan Generation with Panoptic Refinement

• Paper: https://arxiv.org/abs/2207.13268

ManiFest: Manifold Deformation for Few-shot Image Translation

• Paper: https://arxiv.org/abs/2111.13681
• Code: https://github.com/cv-rits/ManiFest

VecGAN: Image-to-Image Translation with Interpretable Latent Directions

• Paper: https://arxiv.org/abs/2207.03411

DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation

• Paper: https://arxiv.org/abs/2207.06124
• Code: https://github.com/Huage001/DynaST

Cross Attention Based Style Distribution for Controllable Person Image Synthesis

• Paper: https://arxiv.org/abs/2208.00712
• Code: GitHub - xyzhouo/CASD

Vector Quantized Image-to-Image Translation

• Paper: https://arxiv.org/abs/2207.13286
• Code: https://github.com/cyj407/VQ-I2I

URUST: Ultra-high-resolution unpaired stain transformation via Kernelized Instance Normalization

• Paper: https://arxiv.org/abs/2208.10730
• Code: https://github.com/Kaminyou/URUST

General Object Pose Transformation Network from Unpaired Data

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/suyukun666/UFO-PT

Unpaired Image Translation via Vector Symbolic Architectures

• Paper: https://arxiv.org/abs/2209.02686
• Code: https://github.com/facebookresearch/vsait

Supervised Attribute Information Removal and Reconstruction for Image Manipulation

• Paper: https://arxiv.org/abs/2207.06555
• Code: https://github.com/NannanLi999/AIRR

Bi-Level Feature Alignment for Versatile Image Translation and Manipulation

• Paper: ECVA | European Computer Vision Association

Multi-Curve Translator for High-Resolution Photorealistic Image Translation

• Paper: ECVA | European Computer Vision Association

CoGS: Controllable Generation and Search from Sketch and Style

• Paper: ECVA | European Computer Vision Association

AgeTransGAN for Facial Age Transformation with Rectified Performance Metrics

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/AvLab-CV/AgeTransGAN

Others for image generation

StyleLight: HDR Panorama Generation for Lighting Estimation and Editing

• Paper: https://arxiv.org/abs/2207.14811
• Code: https://github.com/Wanggcong/StyleLight

Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling

• Paper: https://arxiv.org/abs/2207.02196
• Code: https://github.com/fudan-zvg/PDS

GAN Cocktail: mixing GANs without dataset access

• Paper: https://arxiv.org/abs/2106.03847
• Code: https://github.com/omriav/GAN-cocktail

Compositional Visual Generation with Composable Diffusion Models

• Paper: https://arxiv.org/abs/2206.01714
• Code: https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch

Adaptive-Feature-Interpolation-for-Low-Shot-Image-Generation

• Paper: https://arxiv.org/abs/2112.02450
• Code: https://github.com/dzld00/Adaptive-Feature-Interpolation-for-Low-Shot-Image-Generation

StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pretrained StyleGAN

• Paper: https://arxiv.org/abs/2203.04036
• Code: https://github.com/FeiiYin/StyleHEAT

WaveGAN: An Frequency-aware GAN for High-Fidelity Few-shot Image Generation

• Paper: https://arxiv.org/abs/2207.07288
• Code: https://github.com/kobeshegu/ECCV2022_WaveGAN

FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANs

• Paper: https://arxiv.org/abs/2207.08630
• Code: https://github.com/iceli1007/FakeCLR

Auto-regressive Image Synthesis with Integrated Quantization

• Paper: https://arxiv.org/abs/2207.10776
• Code: https://github.com/fnzhan/IQ-VAE

PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation

• Paper: https://arxiv.org/abs/2204.00833
• Code: https://github.com/BlingHe/PixelFolder

DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta

• Paper: https://arxiv.org/abs/2207.10271
• Code: https://github.com/bcmi/DeltaGAN-Few-Shot-Image-Generation

Generator Knows What Discriminator Should Learn in Unconditional GANs

• Paper: https://arxiv.org/abs/2207.13320
• Code: https://github.com/naver-ai/GGDR

Hierarchical Semantic Regularization of Latent Spaces in StyleGANs

• Paper: https://arxiv.org/abs/2208.03764
• Code: https://drive.google.com/file/d/1gzHTYTgGBUlDWyN_Z3ORofisQrHChg_n/view

FurryGAN: High Quality Foreground-aware Image Synthesis

• Paper: https://arxiv.org/abs/2208.10422
• Project: FurryGAN

Improving GANs for Long-Tailed Data through Group Spectral Regularization

• Paper: https://arxiv.org/abs/2208.09932
• Code: https://drive.google.com/file/d/1aG48i04Q8mOmD968PAgwEvPsw1zcS4Gk/view

Exploring Gradient-based Multi-directional Controls in GANs

• Paper: https://arxiv.org/abs/2209.00698
• Code: https://github.com/zikuncshelly/GradCtrl

Improved Masked Image Generation with Token-Critic

• Paper: https://arxiv.org/abs/2209.04439

Weakly-Supervised Stitching Network for Real-World Panoramic Image Generation

• Paper: https://arxiv.org/abs/2209.05968
• Project: Weakly-Supervised Stitching Network for Real-World Panoramic Image Generation

Any-Resolution Training for High-Resolution Image Synthesis

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/chail/anyres-gan

BIPS: Bi-modal Indoor Panorama Synthesis via Residual Depth-Aided Adversarial Learning

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/chang9711/BIPS

Few-Shot Image Generation with Mixup-Based Distance Learning

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/reyllama/mixdl

StyleGAN-Human: A Data-Centric Odyssey of Human Generation

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/stylegan-human/StyleGAN-Human

StyleFace: Towards Identity-Disentangled Face Generation on Megapixels

• Paper: ECVA | European Computer Vision Association

Contrastive Learning for Diverse Disentangled Foreground Generation

• Paper: ECVA | European Computer Vision Association

BLT: Bidirectional Layout Transformer for Controllable Layout Generation

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/google-research/google-research/tree/master/layout-blt

Entropy-Driven Sampling and Training Scheme for Conditional Diffusion Generation

• Paper: https://arxiv.org/abs/2206.11474
• Code: https://github.com/ZGCTroy/ED-DPM

Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes

• Paper: ECVA | European Computer Vision Association

DuelGAN: A Duel between Two Discriminators Stabilizes the GAN Training

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/UCSC-REAL/DuelGAN

Video Generation

Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer

• Paper: https://arxiv.org/abs/2204.03638
• Code: https://github.com/SongweiGe/TATS

Controllable Video Generation through Global and Local Motion Dynamics

• Paper: https://arxiv.org/abs/2204.06558
• Code: GitHub - Araachie/glass: Controllable Video Generation through Global and Local Motion Dynamics. In ECCV, 2022

Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesis

• Paper: https://arxiv.org/abs/2207.05049
• Code: https://github.com/fast-vid2vid/fast-vid2vid

Synthesizing Light Field Video from Monocular Video

• Paper: https://arxiv.org/abs/2207.10357
• Code: https://github.com/ShrisudhanG/Synthesizing-Light-Field-Video-from-Monocular-Video

StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation

• Paper: https://arxiv.org/abs/2209.06192
• Code: https://github.com/adymaharana/storydalle

Motion Transformer for Unsupervised Image Animation

• Paper:
• Code: https://github.com/JialeTao/MoTrans

Sound-Guided Semantic Video Generation

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/anonymous5584/sound-guided-semantic-video-generation

Layered Controllable Video Generation

• Paper: https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4847_ECCV_2022_paper.php

Diverse Generation from a Single Video Made Possible

• Paper: https://arxiv.org/abs/2109.08591
• Code: https://github.com/nivha/single_video_generation

Semantic-Aware Implicit Neural Audio-Driven Video Portrait Generation

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/alvinliu0/SSP-NeRF

EAGAN: Efficient Two-Stage Evolutionary Architecture Search for GANs

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/marsggbo/EAGAN

BlobGAN: Spatially Disentangled Scene Representations

• Paper: https://arxiv.org/abs/2205.02837
• Code: https://github.com/dave-epstein/blobgan

Others

Learning Local Implicit Fourier Representation for Image Warping

• Paper: https://ipl.dgist.ac.kr/LTEW.pdf
• Code: https://github.com/jaewon-lee-b/ltew
• Tags: Image Warping

Dress Code: High-Resolution Multi-Category Virtual Try-On

• Paper: https://arxiv.org/abs/2204.08532
• Code: https://github.com/aimagelab/dress-code
• Tags: Virtual Try-On

High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions

• Paper: https://arxiv.org/abs/2206.14180
• Code: https://github.com/sangyun884/HR-VITON
• Tags: Virtual Try-On

Single Stage Virtual Try-on via Deformable Attention Flows

• Paper: https://arxiv.org/abs/2207.09161
• Tags: Virtual Try-On

Outpainting by Queries

• Paper: https://arxiv.org/abs/2207.05312
• Code: https://github.com/Kaiseem/QueryOTR
• Tags: Outpainting

Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal

• Paper: https://arxiv.org/abs/2207.08178
• Code: https://github.com/thinwayliu/Watermark-Vaccine
• Tags: Watermark Protection

Efficient Meta-Tuning for Content-aware Neural Video Delivery

• Paper: https://arxiv.org/abs/2207.09691
• Code: https://github.com/Neural-video-delivery/EMT-Pytorch-ECCV2022
• Tags: Video Delivery

Human-centric Image Cropping with Partition-aware and Content-preserving Features

• Paper: https://arxiv.org/abs/2207.10269
• Code: https://github.com/bcmi/Human-Centric-Image-Cropping

CelebV-HQ: A Large-Scale Video Facial Attributes Dataset

• Paper: https://arxiv.org/abs/2207.12393
• Code: https://github.com/CelebV-HQ/CelebV-HQ
• Tags: Dataset

Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis

• Paper: https://arxiv.org/abs/2207.11770
• Code: https://github.com/sstzal/DFRF
• Tags: Talking Head Synthesis

Responsive Listening Head Generation: A Benchmark Dataset and Baseline

• Paper: https://arxiv.org/abs/2112.13548
• Code: https://github.com/dc3ea9f/vico_challenge_baseline

Contrastive Monotonic Pixel-Level Modulation

• Paper: https://arxiv.org/abs/2207.11517
• Code: https://github.com/lukun199/MonoPix

AutoTransition: Learning to Recommend Video Transition Effects

• Paper: https://arxiv.org/abs/2207.13479
• Code: https://github.com/acherstyx/AutoTransition

Bringing Rolling Shutter Images Alive with Dual Reversed Distortion

• Paper: https://arxiv.org/abs/2203.06451
• Code: https://github.com/zzh-tech/Dual-Reversed-RS

Learning Object Placement via Dual-path Graph Completion

• Paper: https://arxiv.org/abs/2207.11464
• Code: https://github.com/bcmi/GracoNet-Object-Placement

DeepMCBM: A Deep Moving-camera Background Model

• Paper: https://arxiv.org/abs/2209.07923
• Code: https://github.com/BGU-CS-VIL/DeepMCBM

Mind the Gap in Distilling StyleGANs

• Paper: https://arxiv.org/abs/2208.08840
• Code: https://github.com/xuguodong03/StyleKD

StyleSwap: Style-Based Generator Empowers Robust Face Swapping

• Paper: https://arxiv.org/abs/2209.13514
• Code: https://github.com/Seanseattle/StyleSwap
• Tags: Face Swapping

Geometric Representation Learning for Document Image Rectification

• Paper: ECVA | European Computer Vision Association
• Code: https://github.com/fh2019ustc/DocGeoNet
• Tags: Document Image Rectification

Studying Bias in GANs through the Lens of Race

• Paper: ECVA | European Computer Vision Association
• Tags: Racial Bias

On the Robustness of Quality Measures for GANs

• Paper: https://arxiv.org/abs/2201.13019
• Code: https://github.com/MotasemAlfarra/R-FID-Robustness-of-Quality-Measures-for-GANs

TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN Evaluation

• Paper: ECVA | European Computer Vision Association
• Tags: GAN Evaluation

AAAI2022-Low-Level-Vision

Image Restoration - 图像恢复

Unsupervised Underwater Image Restoration: From a Homology Perspective

• Paper: AAAI2022: Unsupervised Underwater Image Restoration: From a Homology Perspective
• Tags: Underwater Image Restoration

Panini-Net: GAN Prior based Degradation-Aware Feature Interpolation for Face Restoration

• Paper: AAAI2022: Panini-Net: GAN Prior Based Degradation-Aware Feature Interpolation for Face Restoration
• Code: GitHub - wyhuai/Panini-Net: [AAAI 2022] Panini-Net: GAN Prior based Degradation-Aware Feature Interpolation for Face Restoration
• Tags: Face Restoration

Burst Restoration

Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers

• Paper: AAAI2022: SiamTrans: Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers
• Code: https://github.com/laulampaul/siamtrans

Video Restoration

Transcoded Video Restoration by Temporal Spatial Auxiliary Network

• Paper: AAAI2022: Transcoded Video Restoration by Temporal Spatial Auxiliary Network
• Tags: Transcoded Video Restoration

Super Resolution - 超分辨率

Image Super Resolution

SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution

• Paper: AAAI2022: SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution

Efficient Non-Local Contrastive Attention for Image Super-Resolution

• Paper: https://arxiv.org/abs/2201.03794
• Code: GitHub - Zj-BinXia/ENLCA: This project is official implementation of 'Efficient Non-Local Contrastive Attention for Image Super-Resolution', AAAI2022

Best-Buddy GANs for Highly Detailed Image Super-Resolution

• Paper: AAAI2022: Best-Buddy GANs for Highly Detailed Image Super-Resolution
• Tags: GAN

Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution

• Paper: AAAI2022: Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution
• Tags: Text SR

Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-Based Super-Resolution

• Paper: AAAI2022: Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-Based Super-Resolution
• Code: GitHub - Zj-BinXia/AMSA: This project is the official implementation of 'Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-Resolution', AAAI2022
• Tags: Reference-Based SR

Detail-Preserving Transformer for Light Field Image Super-Resolution

• Paper: AAAI2022: Detail-Preserving Transformer for Light Field Image Super-Resolution
• Tags: Light Field

Denoising - 去噪

Image Denoising

Generative Adaptive Convolutions for Real-World Noisy Image Denoising

• Paper: AAAI2022: Generative Adaptive Convolutions for Real-World Noisy Image Denoising

Video Denoising

ReMoNet: Recurrent Multi-Output Network for Efficient Video Denoising

• Paper: AAAI2022: ReMoNet: Recurrent Multi-Output Network for Efficient Video Denoising

Deblurring - 去模糊

Video Deblurring

Deep Recurrent Neural Network with Multi-Scale Bi-Directional Propagation for Video Deblurring

• Paper: AAAI2022: Deep Recurrent Neural Network with Multi-Scale Bi-Directional Propagation for Video Deblurring

Deraining - 去雨

Online-Updated High-Order Collaborative Networks for Single Image Deraining

• Paper: AAAI2022: ReMoNet: Recurrent Multi-Output Network for Efficient Video Denoising

Close the Loop: A Unified Bottom-up and Top-down Paradigm for Joint Image Deraining and Segmentation

• Paper: AAAI2022: Close the Loop: A Unified Bottom-up and Top-down Paradigm for Joint Image Deraining and Segmentation
• Tags: Joint Image Deraining and Segmentation

Dehazing - 去雾

Uncertainty-Driven Dehazing Network

• Paper: AAAI2022: Uncertainty-Driven Dehazing Network

Demosaicing - 去马赛克

Deep Spatial Adaptive Network for Real Image Demosaicing

• Paper: AAAI2022: Deep Spatial Adaptive Network for Real Image Demosaicing

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework Using Self-Supervised Multi-Task Learning

• Paper: https://arxiv.org/abs/2112.01030
• Code: https://github.com/miccaiif/TransMEF

Image Enhancement - 图像增强

Low-Light Image Enhancement

Low-Light Image Enhancement with Normalizing Flow

• Paper: https://arxiv.org/abs/2109.05923
• Code: https://github.com/wyf0912/LLFlow

Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement

• Paper: AAAI2022: Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement

Semantically Contrastive Learning for Low-Light Image Enhancement

• Paper: AAAI2022: Semantically Contrastive Learning for Low-Light Image Enhancement
• Tags: contrastive learning

Image Matting - 图像抠图

MODNet: Trimap-Free Portrait Matting in Real Time

• Paper: https://arxiv.org/abs/2011.11961
• Code: https://github.com/ZHKKKe/MODNet

Shadow Removal - 阴影消除

Efficient Model-Driven Network for Shadow Removal

• Paper: AAAI2022: Efficient Model-Driven Network for Shadow Removal

Image Compression - 图像压缩

Towards End-to-End Image Compression and Analysis with Transformers

• Paper: https://arxiv.org/abs/2112.09300
• Code: https://github.com/BYchao100/Towards-Image-Compression-and-Analysis-with-Transformers
• Tags: Transformer

OoDHDR-Codec: Out-of-Distribution Generalization for HDR Image Compression

• Paper: AAAI2022: OoDHDR-Codec: Out-of-Distribution Generalization for HDR Image Compression

Two-Stage Octave Residual Network for End-to-End Image Compression

• Paper: AAAI2022: Two-Stage Octave Residual Network for End-to-End Image Compression

Image Quality Assessment - 图像质量评价

Content-Variant Reference Image Quality Assessment via Knowledge Distillation

• Paper: AAAI2022: Content-Variant Reference Image Quality Assessment via Knowledge Distillation

Perceptual Quality Assessment of Omnidirectional Images

• Paper: AAAI2022: Perceptual Quality Assessment of Omnidirectional Images
• Tags: Omnidirectional Images

Style Transfer - 风格迁移

Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization

• Paper: https://arxiv.org/abs/2103.11784
• Code: GitHub - czczup/URST: [AAAI 2022] Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization

Deep Translation Prior: Test-Time Training for Photorealistic Style Transfer

• Paper: AAAI2022: Deep Translation Prior: Test-Time Training for Photorealistic Style Transfer

Image Editing - 图像编辑

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal

• Paper: AAAI2022: SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal
• Code: https://github.com/Snowfallingplum/SSAT
• Tags: Makeup Transfer and Removal

Assessing a Single Image in Reference-Guided Image Synthesis

• Paper: AAAI2022: Assessing a Single Image in Reference-Guided Image Synthesis

Interactive Image Generation with Natural-Language Feedback

• Paper: AAAI2022: Interactive Image Generation with Natural-Language Feedback

PetsGAN: Rethinking Priors for Single Image Generation

• Paper: AAAI2022: PetsGAN: Rethinking Priors for Single Image Generation

Pose Guided Image Generation from Misaligned Sources via Residual Flow Based Correction

• Paper: AAAI2022: Pose Guided Image Generation from Misaligned Sources via Residual Flow Based Correction

Hierarchical Image Generation via Transformer-Based Sequential Patch Selection

• Paper: AAAI2022: Hierarchical Image Generation via Transformer-Based Sequential Patch Selection

Style-Guided and Disentangled Representation for Robust Image-to-Image Translation

• Paper: AAAI2022: Style-Guided and Disentangled Representation for Robust Image-to-Image Translation

OA-FSUI2IT: A Novel Few-Shot Cross Domain Object Detection Framework with Object-Aware Few-shot Unsupervised Image-to-Image Translation

• Paper: AAAI2022: OA-FSUI2IT: A Novel Few-Shot Cross Domain Object Detection Framework with Object-Aware Few-shot Unsupervised Image-to-Image Translation
• Code: https://github.com/emdata-ailab/FSCD-Det
• Tags: Image-to-Image Translation used for Object Detection

Video Generation

Learning Temporally and Semantically Consistent Unpaired Video-to-Video Translation through Pseudo-Supervision from Synthetic Optical Flow

• Paper: AAAI2022: Learning Temporally and Semantically Consistent Unpaired Video-to-Video Translation through Pseudo-Supervision from Synthetic Optical Flow
• Code: GitHub - wangkaihong/Unsup_Recycle_GAN: Code for "Learning Temporally and Semantically Consistent Unpaired Video-to-video Translation Through Pseudo-Supervision From Synthetic Optical Flow", AAAI 2022

参考

什么是low-level、high-level任务_low-level任务_WTHunt的博客-CSDN博客

在 CV 领域里 low-level vision 前景怎么样？ - 知乎 (zhihu.com)

GitHub - DarrenPan/Awesome-CVPR2023-Low-Level-Vision: A Collection of Papers and Codes in CVPR2023/2022 about low level vision

• Awesome-CVPR2022-Low-Level-Vision
• Awesome-ECCV2022-Low-Level-Vision
• Awesome-AAAI2022-Low-Level-Vision
• Awesome-NeurIPS2021-Low-Level-Vision
• Awesome-ICCV2021-Low-Level-Vision
• Awesome-CVPR2021/CVPR2020-Low-Level-Vision
• Awesome-ECCV2020-Low-Level-Vision