Awesome-CVPR2024-Low-Level-Vision icon indicating copy to clipboard operation
Awesome-CVPR2024-Low-Level-Vision copied to clipboard

Published 20 hours ago • verified publisher icon DarrenPan
→

Metadata

A Collection of Papers and Codes in CVPR2023/2022 about low level vision

CVPR2022-Low-Level-Vision

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

Related collections for low-level vision

  • 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

  • NITRE

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: 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

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

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
  • 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/2203.09388
  • Tags: Guided SR

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

  • Paper: https://arxiv.org/abs/2203.09388
  • 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

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

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

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

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

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

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: 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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

← Metadata

627
Stars
49
Forks
Watchers

Owner

verified publisher icon DarrenPan

Metadata

A Collection of Papers and Codes in CVPR2023/2022 about low level vision

Back