CVPR2022-Low-Level-Vision.md

CVPR2022-Low-Level-Vision

A Collection of Papers and Codes in CVPR2022 related to Low-Level Vision

[Completed] If you find some missing papers or typos, feel free to pull issues or requests.

Related collections for 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

Catalogue

• Image Restoration

  • Burst Restoration
  • Video Restoration
  • Hyperspectral Image Reconstruction

• Super Resolution

  • Image Super Resolution
  • Video Super Resolution

• Image Rescaling

• Denoising

  • Image Denoising
  • Burst Denoising
  • Video Denoising

• Deblurring

  • Image Deblurring
  • Video Deblurring

• Deraining

• Dehazing

• Demoireing

• Frame Interpolation

  • Spatial-Temporal Video Super-Resolution

• Image Enhancement

  • Low-Light Image Enhancement

• Image Harmonization

• Image Completion/Inpainting

  • Video Inpainting

• Image Matting

• Shadow Removal

• Relighting

• Image Stitching

• Image Compression

• Image Quality Assessment

• Image Decomposition

• Style Transfer

• Image Editing

• Image Generation/Synthesis

  • Video Generation/Synthesis

• Others

• NTIRE

Image Restoration - 图像恢复 [back]

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: https://openaccess.thecvf.com/content/CVPR2022/html/Wang_Self-Supervised_Deep_Image_Restoration_via_Adaptive_Stochastic_Gradient_Langevin_Dynamics_CVPR_2022_paper.html
• Tags: Self-Supervised

KNN Local Attention for Image Restoration

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Lee_KNN_Local_Attention_for_Image_Restoration_CVPR_2022_paper.html
• Code: https://sites.google.com/view/cvpr22-kit

GIQE: Generic Image Quality Enhancement via Nth Order Iterative Degradation

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Shyam_GIQE_Generic_Image_Quality_Enhancement_via_Nth_Order_Iterative_Degradation_CVPR_2022_paper.html

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: https://openaccess.thecvf.com/content/CVPR2022/html/Zhao_Rethinking_Deep_Face_Restoration_CVPR_2022_paper.html
• Tags: Face

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Wang_RestoreFormer_High-Quality_Blind_Face_Restoration_From_Undegraded_Key-Value_Pairs_CVPR_2022_paper.html
• Code: https://github.com/wzhouxiff/RestoreFormer
• Tags: Face

Blind Face Restoration via Integrating Face Shape and Generative Priors

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Zhu_Blind_Face_Restoration_via_Integrating_Face_Shape_and_Generative_Priors_CVPR_2022_paper.html
• Tags: Face

Global Sensing and Measurements Reuse for Image Compressed Sensing

• Paper: https://arxiv.org/abs/2206.11629
• Code: https://github.com/fze0012/MR-CCSNet
• Tags: Compressed Sensing

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: https://github.com/GuoShi28/2StageAlign
• 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: https://github.com/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 [back]

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: https://github.com/greatlog/UnpairedSR
• Tags: Blind SR

Deep Constrained Least Squares for Blind Image Super-Resolution

• Paper: https://arxiv.org/abs/2202.07508
• Code: https://github.com/Algolzw/DCLS
• 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: https://github.com/lonelyhope/DADA
• Tags: Real SR

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Guo_LAR-SR_A_Local_Autoregressive_Model_for_Image_Super-Resolution_CVPR_2022_paper.html

Texture-Based Error Analysis for Image Super-Resolution

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Magid_Texture-Based_Error_Analysis_for_Image_Super-Resolution_CVPR_2022_paper.html

Learning to Zoom Inside Camera Imaging Pipeline

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Tang_Learning_To_Zoom_Inside_Camera_Imaging_Pipeline_CVPR_2022_paper.html
• Tags: Raw-to-Raw domain

Task Decoupled Framework for Reference-Based Super-Resolution

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Huang_Task_Decoupled_Framework_for_Reference-Based_Super-Resolution_CVPR_2022_paper.html
• 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: https://github.com/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: https://openaccess.thecvf.com/content/CVPR2022/html/Yoon_SphereSR_360deg_Image_Super-Resolution_With_Arbitrary_Projection_via_Continuous_Spherical_CVPR_2022_paper.html

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: https://github.com/centreborelli/HDR-DSP-SR/
• 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: https://github.com/ckkelvinchan/BasicVSR_PlusPlus

Learning Trajectory-Aware Transformer for Video Super-Resolution

• Paper: https://arxiv.org/abs/2204.04216
• Code: https://github.com/researchmm/TTVSR
• 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: https://openaccess.thecvf.com/content/CVPR2022/html/Yu_Memory-Augmented_Non-Local_Attention_for_Video_Super-Resolution_CVPR_2022_paper.html

Stable Long-Term Recurrent Video Super-Resolution

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Chiche_Stable_Long-Term_Recurrent_Video_Super-Resolution_CVPR_2022_paper.html

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 [back]

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: https://openaccess.thecvf.com/content/CVPR2022/html/Zhong_Faithful_Extreme_Rescaling_via_Generative_Prior_Reciprocated_Invertible_Representations_CVPR_2022_paper.html
• Code: https://github.com/cszzx/GRAIN

Denoising - 去噪 [back]

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: https://github.com/Reyhanehne/CVF-SID_PyTorch
• Tags: Self-Supervised

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Kim_Noise_Distribution_Adaptive_Self-Supervised_Image_Denoising_Using_Tweedie_Distribution_and_CVPR_2022_paper.html
• 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: https://openaccess.thecvf.com/content/CVPR2022/html/Zou_Estimating_Fine-Grained_Noise_Model_via_Contrastive_Learning_CVPR_2022_paper.html
• 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 [back]

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: https://openaccess.thecvf.com/content/CVPR2022/html/Zhang_Pixel_Screening_Based_Intermediate_Correction_for_Blind_Deblurring_CVPR_2022_paper.html
• Tags: Blind

Deblurring via Stochastic Refinement

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Whang_Deblurring_via_Stochastic_Refinement_CVPR_2022_paper.html

XYDeblur: Divide and Conquer for Single Image Deblurring

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Ji_XYDeblur_Divide_and_Conquer_for_Single_Image_Deblurring_CVPR_2022_paper.html

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 [back]

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: https://openaccess.thecvf.com/content/CVPR2022/html/Zou_Dreaming_To_Prune_Image_Deraining_Networks_CVPR_2022_paper.html

Dehazing - 去雾 [back]

Self-augmented Unpaired Image Dehazing via Density and Depth Decomposition

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Yang_Self-Augmented_Unpaired_Image_Dehazing_via_Density_and_Depth_Decomposition_CVPR_2022_paper.html
• Code: https://github.com/YaN9-Y/D4
• Tags: Unpaired

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Liu_Towards_Multi-Domain_Single_Image_Dehazing_via_Test-Time_Training_CVPR_2022_paper.html

Image Dehazing Transformer With Transmission-Aware 3D Position Embedding

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Guo_Image_Dehazing_Transformer_With_Transmission-Aware_3D_Position_Embedding_CVPR_2022_paper.html

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Li_Physically_Disentangled_Intra-_and_Inter-Domain_Adaptation_for_Varicolored_Haze_Removal_CVPR_2022_paper.html

Demoireing - 去摩尔纹 [back]

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 [back]

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: https://github.com/ltkong218/IFRNet

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 [back]

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: https://github.com/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: https://github.com/vis-opt-group/SCI

Deep Color Consistent Network for Low-Light Image Enhancement

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Zhang_Deep_Color_Consistent_Network_for_Low-Light_Image_Enhancement_CVPR_2022_paper.html

SNR-Aware Low-Light Image Enhancement

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Xu_SNR-Aware_Low-Light_Image_Enhancement_CVPR_2022_paper.html
• Code: https://github.com/dvlab-research/SNR-Aware-Low-Light-Enhance

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Wu_URetinex-Net_Retinex-Based_Deep_Unfolding_Network_for_Low-Light_Image_Enhancement_CVPR_2022_paper.html

Image Harmonization - 图像协调 [back]

High-Resolution Image Harmonization via Collaborative Dual Transformationsg

• Paper: https://arxiv.org/abs/2109.06671
• Code: https://github.com/bcmi/CDTNet-High-Resolution-Image-Harmonization

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

• Paper: https://arxiv.org/abs/2204.13962
• Code: https://github.com/YCHang686/SCS-Co-CVPR2022

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 [back]

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: https://github.com/DQiaole/ZITS_inpainting

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

• Paper: https://arxiv.org/abs/2203.06304
• Code: https://github.com/tsingqguo/misf

MAT: Mask-Aware Transformer for Large Hole Image Inpainting

• Paper: https://arxiv.org/abs/2203.15270
• Code: https://github.com/fenglinglwb/MAT

Reduce Information Loss in Transformers for Pluralistic Image Inpainting

• Paper: https://arxiv.org/abs/2205.05076
• Code: https://github.com/liuqk3/PUT

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

• Paper: https://arxiv.org/abs/2201.09865
• Code: https://github.com/andreas128/RePaint
• Tags: DDPM

Dual-Path Image Inpainting With Auxiliary GAN Inversion

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Wang_Dual-Path_Image_Inpainting_With_Auxiliary_GAN_Inversion_CVPR_2022_paper.html

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: https://openaccess.thecvf.com/content/CVPR2022/html/Szeto_The_DEVIL_Is_in_the_Details_A_Diagnostic_Evaluation_Benchmark_CVPR_2022_paper.html
• Code: https://github.com/MichiganCOG/devil

DLFormer: Discrete Latent Transformer for Video Inpainting

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Ren_DLFormer_Discrete_Latent_Transformer_for_Video_Inpainting_CVPR_2022_paper.html

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 [back]

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: https://github.com/nowsyn/InstMatt

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 [back]

Bijective Mapping Network for Shadow Removal

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Zhu_Bijective_Mapping_Network_for_Shadow_Removal_CVPR_2022_paper.html

Relighting

Face Relighting with Geometrically Consistent Shadows

• Paper: https://arxiv.org/abs/2203.16681
• Code: https://github.com/andrewhou1/GeomConsistentFR
• 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 [back]

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: https://openaccess.thecvf.com/content/CVPR2022/html/Li_Automatic_Color_Image_Stitching_Using_Quaternion_Rank-1_Alignment_CVPR_2022_paper.html

Geometric Structure Preserving Warp for Natural Image Stitching

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Du_Geometric_Structure_Preserving_Warp_for_Natural_Image_Stitching_CVPR_2022_paper.html

Image Compression - 图像压缩 [back]

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: https://github.com/xiaosu-zhu/McQuic

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: https://openaccess.thecvf.com/content/CVPR2022/html/Kim_Joint_Global_and_Local_Hierarchical_Priors_for_Learned_Image_Compression_CVPR_2022_paper.html

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Rhee_LC-FDNet_Learned_Lossless_Image_Compression_With_Frequency_Decomposition_Network_CVPR_2022_paper.html

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: https://openaccess.thecvf.com/content/CVPR2022/html/Wodlinger_SASIC_Stereo_Image_Compression_With_Latent_Shifts_and_Stereo_Attention_CVPR_2022_paper.html
• Tags: Stereo Image Compression

Deep Stereo Image Compression via Bi-Directional Coding

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Lei_Deep_Stereo_Image_Compression_via_Bi-Directional_Coding_CVPR_2022_paper.html
• Tags: Stereo Image Compression

Learning Based Multi-Modality Image and Video Compression

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Lu_Learning_Based_Multi-Modality_Image_and_Video_Compression_CVPR_2022_paper.html

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: https://openaccess.thecvf.com/content/CVPR2022/html/Chen_LSVC_A_Learning-Based_Stereo_Video_Compression_Framework_CVPR_2022_paper.html
• 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 [back]

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: https://github.com/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 [back]

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Das_PIE-Net_Photometric_Invariant_Edge_Guided_Network_for_Intrinsic_Image_Decomposition_CVPR_2022_paper.html
• Code: https://github.com/Morpheus3000/PIE-Net

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 [back]

CLIPstyler: Image Style Transfer with a Single Text Condition

• Paper: https://arxiv.org/abs/2112.00374
• Code: https://github.com/cyclomon/CLIPstyler
• Tags: CLIP

Style-ERD: Responsive and Coherent Online Motion Style Transfer

• Paper: https://arxiv.org/abs/2203.02574
• Code: https://github.com/tianxintao/Online-Motion-Style-Transfer

Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

• Paper: https://arxiv.org/abs/2203.07740
• Code: https://github.com/YBZh/EFDM

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: https://openaccess.thecvf.com/content/CVPR2022/html/Deng_StyTr2_Image_Style_Transfer_With_Transformers_CVPR_2022_paper.html

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

• Paper: https://arxiv.org/abs/2203.13452
• Code: https://github.com/chiutaiyin/PCA-Knowledge-Distillation

Image Editing - 图像编辑 [back]

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: https://github.com/wty-ustc/HairCLIP
• Tags: CLIP

HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing

• Paper: https://arxiv.org/abs/2111.15666
• Code: https://github.com/yuval-alaluf/hyperstyle

Blended Diffusion for Text-driven Editing of Natural Images

• Paper: https://arxiv.org/abs/2111.14818
• Code: https://github.com/omriav/blended-diffusion
• 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: https://github.com/BillyXYB/TransEditor

HyperInverter: Improving StyleGAN Inversion via Hypernetwork

• Paper: https://arxiv.org/abs/2112.00719
• Code: https://github.com/VinAIResearch/HyperInverter

Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing

• Paper: https://arxiv.org/abs/2206.08357
• Code: https://github.com/adobe-research/sam_inversion

Brain-Supervised Image Editing

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Davis_Brain-Supervised_Image_Editing_CVPR_2022_paper.html

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Shi_SpaceEdit_Learning_a_Unified_Editing_Space_for_Open-Domain_Image_Color_CVPR_2022_paper.html

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 [back]

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

Text to Image Generation with Semantic-Spatial Aware GAN

• Paper: https://arxiv.org/abs/2104.00567
• Code: https://github.com/wtliao/text2image

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: https://github.com/tobran/DF-GAN

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: https://github.com/gwang-kim/DiffusionCLIP

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

• Paper: https://arxiv.org/abs/2111.13333
• Code: https://github.com/zipengxuc/PPE-Pytorch

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: https://openaccess.thecvf.com/content/CVPR2022/html/Wu_Text-to-Image_Synthesis_Based_on_Object-Guided_Joint-Decoding_Transformer_CVPR_2022_paper.html

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: https://github.com/sapphire497/query-selected-attention

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: https://github.com/fnzhan/UNITE

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: https://github.com/jcy132/Hneg_SRC

Neural Texture Extraction and Distribution for Controllable Person Image Synthesis

• Paper: https://arxiv.org/abs/2204.06160
• Code: https://github.com/RenYurui/Neural-Texture-Extraction-Distribution

Unpaired Cartoon Image Synthesis via Gated Cycle Mapping

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Men_Unpaired_Cartoon_Image_Synthesis_via_Gated_Cycle_Mapping_CVPR_2022_paper.html

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Punnappurath_Day-to-Night_Image_Synthesis_for_Training_Nighttime_Neural_ISPs_CVPR_2022_paper.html
• Code: https://github.com/SamsungLabs/day-to-night

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Guo_Alleviating_Semantics_Distortion_in_Unsupervised_Low-Level_Image-to-Image_Translation_via_Structure_CVPR_2022_paper.html

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Zhang_Wavelet_Knowledge_Distillation_Towards_Efficient_Image-to-Image_Translation_CVPR_2022_paper.html

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Ko_Self-Supervised_Dense_Consistency_Regularization_for_Image-to-Image_Translation_CVPR_2022_paper.html

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

• Paper: https://arxiv.org/abs/2103.15545
• Project Web: https://www.wisdom.weizmann.ac.il/~vision/gpnn/
• Tags: Image manipulation

HairMapper: Removing Hair From Portraits Using GANs

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Wu_HairMapper_Removing_Hair_From_Portraits_Using_GANs_CVPR_2022_paper.html

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: https://github.com/fnzhan/MoNCE

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: https://github.com/lucidrains/RQ-Transformer

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: https://github.com/PangzeCheung/Dual-task-Pose-Transformer-Network

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

• Paper: https://arxiv.org/abs/2112.10762
• Code: https://github.com/microsoft/StyleSwin

Semantic-shape Adaptive Feature Modulation for Semantic Image Synthesis

• Paper: https://arxiv.org/abs/2203.16898
• Code: https://github.com/cszy98/SAFM

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: https://github.com/Shi-Yupeng/RESAIL-For-SIS

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: https://github.com/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: https://openaccess.thecvf.com/content/CVPR2022/html/Xie_Learning_To_Memorize_Feature_Hallucination_for_One-Shot_Image_Generation_CVPR_2022_paper.html

Local Attention Pyramid for Scene Image Generation

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Shim_Local_Attention_Pyramid_for_Scene_Image_Generation_CVPR_2022_paper.html

High-Resolution Image Synthesis with Latent Diffusion Models

• Paper: https://arxiv.org/abs/2112.10752
• Code: https://github.com/CompVis/latent-diffusion

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: https://openaccess.thecvf.com/content/CVPR2022/html/Chen_SphericGAN_Semi-Supervised_Hyper-Spherical_Generative_Adversarial_Networks_for_Fine-Grained_Image_Synthesis_CVPR_2022_paper.html

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

• Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Chen_DPGEN_Differentially_Private_Generative_Energy-Guided_Network_for_Natural_Image_Synthesis_CVPR_2022_paper.html

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: https://openaccess.thecvf.com/content/CVPR2022/html/Kim_Polymorphic-GAN_Generating_Aligned_Samples_Across_Multiple_Domains_With_Learned_Morph_CVPR_2022_paper.html

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: https://github.com/FriedRonaldo/Primitives-PS

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: https://github.com/yoyo-nb/Thin-Plate-Spline-Motion-Model

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

• Paper: https://arxiv.org/abs/2112.02815
• Code: https://github.com/Youncy-Hu/MAGE

Diverse Video Generation from a Single Video

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

Others [back]

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: https://github.com/imdumpl78/IHN

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: https://github.com/djosix/IconFlow

Unsupervised Homography Estimation with Coplanarity-Aware GAN

• Paper: https://arxiv.org/abs/2205.03821
• Code: https://github.com/megvii-research/HomoGAN

Diverse Image Outpainting via GAN Inversion

• Paper: https://arxiv.org/abs/2104.00675
• Code: https://github.com/yccyenchicheng/InOut

On Aliased Resizing and Surprising Subtleties in GAN Evaluation

• Paper: https://arxiv.org/abs/2104.11222
• Code: https://github.com/GaParmar/clean-fid

Patch-wise Contrastive Style Learning for Instagram Filter Removal

• Paper: https://arxiv.org/abs/2204.07486
• Code: https://github.com/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: https://github.com/caiyuanhao1998/MST-plus-plus
• 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: https://github.com/IIGROUP/MANIQA
• 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: https://github.com/IIGROUP/AHIQ
• 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: https://github.com/NJU-Jet/FMEN
• 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: https://github.com/xiaom233/BSRN
• 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: https://github.com/NJUVISION/CBUnet
• 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: https://github.com/RenYang-home/NTIRE22_VEnh_SR

Progressive Training of A Two-Stage Framework for Video Restoration

• Paper: https://arxiv.org/abs/2204.09924
• Code: https://github.com/ryanxingql/winner-ntire22-vqe
• 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: https://github.com/chaineypung/CVPR-NTIRE2022-Parallel-Interactive-Transformer-PAIT
• 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