ICCV2021-Low-Level-Vision.md

Awesome-ICCV2021-Low-Level-Vision

A Collection of Papers and Codes in ICCV2021 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-CVPR2023/2022-Low-Level-Vision
• Awesome-NeurIPS2022/2021-Low-Level-Vision
• Awesome-ECCV2022-Low-Level-Vision
• Awesome-AAAI2022-Low-Level-Vision
• Awesome-CVPR2021/2020-Low-Level-Vision
• Awesome-ECCV2020-Low-Level-Vision

Catalogue

• Image Restoration

  • Video Restoration

• Super Resolution

  • Image Super Resolution
  • Video Super Resolution

• Image Rescaling

• Denoising

  • Image Denoising
  • Video Denoising

• Deblurring

  • Image Deblurring
  • Video Deblurring

• Deraining

• HDR Imaging / Multi-Exposure Image Fusion

• Frame Interpolation

• Image Enhancement

  • Low-Light Image Enhancement

• Image Harmonization

• Image Completion/Inpainting

• Image Matting

• Image Stitching

• Image Compression

• Image Quality Assessment

• Style Transfer

• Image Editing

• Image Generation/Synthesis/ Image-to-Image Translation

  • Video Generation

• Others

Image Restoration - 图像恢复 [back]

Spatially-Adaptive Image Restoration using Distortion-Guided Networks

• Paper：https://arxiv.org/abs/2108.08617
• Code: https://github.com/human-analysis/spatially-adaptive-image-restoration

Dynamic Attentive Graph Learning for Image Restoration

• Paper：https://arxiv.org/abs/2109.06620
• Code：https://github.com/jianzhangcs/DAGL

Searching for Controllable Image Restoration Networks

• Paper: https://arxiv.org/abs/2012.11225

Self-Supervised Cryo-Electron Tomography Volumetric Image Restoration From Single Noisy Volume With Sparsity Constraint

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Yang_Self-Supervised_Cryo-Electron_Tomography_Volumetric_Image_Restoration_From_Single_Noisy_Volume_ICCV_2021_paper.html
• Code: https://github.com/icthrm/SC-Net
• Tags: Self-Supervised, Cryo-Electron Tomography Volumetric

Let's See Clearly: Contaminant Artifact Removal for Moving Cameras

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Li_Lets_See_Clearly_Contaminant_Artifact_Removal_for_Moving_Cameras_ICCV_2021_paper.html

Light Source Guided Single-Image Flare Removal from Unpaired Data

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Qiao_Light_Source_Guided_Single-Image_Flare_Removal_From_Unpaired_Data_ICCV_2021_paper.html
• Tags: Flare Removal

How to Train Neural Networks for Flare Removal

• Paper: https://arxiv.org/abs/2011.12485
• Code: https://github.com/google-research/google-research/tree/master/flare_removal
• Tags: Flare Removal

Location-Aware Single Image Reflection Removal

• Paper: https://arxiv.org/abs/2012.07131
• Code: https://github.com/zdlarr/Location-aware-SIRR
• Tags: Reflection Removal

V-DESIRR: Very Fast Deep Embedded Single Image Reflection Removal

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Prasad_V-DESIRR_Very_Fast_Deep_Embedded_Single_Image_Reflection_Removal_ICCV_2021_paper.html
• Code: https://github.com/ee19d005/vdesirr
• Tags: Reflection Removal

Unsupervised Non-Rigid Image Distortion Removal via Grid Deformation

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Li_Unsupervised_Non-Rigid_Image_Distortion_Removal_via_Grid_Deformation_ICCV_2021_paper.html
• Code: https://github.com/Nianyi-Li/unsupervised-NDIR

Towards Flexible Blind JPEG Artifacts Removal

• Paper: https://arxiv.org/abs/2109.14573
• Code: https://github.com/jiaxi-jiang/FBCNN
• Tags: JPEG Artifacts Removal

Learning Dual Priors for JPEG Compression Artifacts Removal

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Fu_Learning_Dual_Priors_for_JPEG_Compression_Artifacts_Removal_ICCV_2021_paper.html
• Tags: JPEG Artifacts Removal

CANet: A Context-Aware Network for Shadow Removal

• Paper: https://arxiv.org/abs/2108.09894
• Code: https://github.com/Zipei-Chen/CANet
• Tags: Shadow Removal

DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided Network

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Jin_DC-ShadowNet_Single-Image_Hard_and_Soft_Shadow_Removal_Using_Unsupervised_Domain-Classifier_ICCV_2021_paper.html
• Code: https://github.com/jinyeying/DC-ShadowNet-Hard-and-Soft-Shadow-Removal
• Tags: Shadow Removal

Learning To Remove Refractive Distortions From Underwater Images

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Thapa_Learning_To_Remove_Refractive_Distortions_From_Underwater_Images_ICCV_2021_paper.html
• Code: https://github.com/SimronThapa/DG-Net-ICCV2021
• Tags: Underwater, Refraction Removal

ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel Loss

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Chen_ALL_Snow_Removed_Single_Image_Desnowing_Algorithm_Using_Hierarchical_Dual-Tree_ICCV_2021_paper.html
• Code: https://github.com/weitingchen83/ICCV2021-Single-Image-Desnowing-HDCWNet
• Tags: Desnowing

Burst Restoration

Deep Reparametrization of Multi-Frame Super-Resolution and Denoising

• Paper: https://arxiv.org/abs/2108.08286
• Code: https://github.com/goutamgmb/deep-rep

Super Resolution - 超分辨率 [back]

Image Super Resolution

Attention-based Multi-Reference Learning for Image Super-Resolution

• Paper：https://arxiv.org/abs/2108.13697
• Code：https://github.com/marcopesavento/Attention-based-Multi-Reference-Learning-for-Image-Super-Resolution

Learning A Single Network for Scale-Arbitrary Super-Resolution

• Paper：https://arxiv.org/abs/2004.03791
• Code：https://github.com/LongguangWang/ArbSR

Fourier Space Losses for Efficient Perceptual Image Super-Resolution

• Paper：https://arxiv.org/abs/2106.00783

Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Magid_Dynamic_High-Pass_Filtering_and_Multi-Spectral_Attention_for_Image_Super-Resolution_ICCV_2021_paper.html
• Code: https://github.com/sabdelmagid/DFSA_ICCV21

Context Reasoning Attention Network for Image Super-Resolution

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Zhang_Context_Reasoning_Attention_Network_for_Image_Super-Resolution_ICCV_2021_paper.html
• Code(Unofficial): https://github.com/Ast-363/CRAN

Learning Frequency-aware Dynamic Network for Efficient Super-Resolution

• Paper: https://arxiv.org/abs/2103.08357
• Code(Unofficial): https://github.com/songyonger/FADN

Benchmarking Ultra-High-Definition Image Super-Resolution

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Zhang_Benchmarking_Ultra-High-Definition_Image_Super-Resolution_ICCV_2021_paper.html
• Code: https://github.com/HDCVLab/UHD4K_UHD8K

Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution

• Code：https://github.com/JingyunLiang/MANet
• Code: https://arxiv.org/abs/2108.05302
• Tags: Blind SR

Designing a Practical Degradation Model for Deep Blind Image Super-Resolution

• Paper：https://arxiv.org/abs/2103.14006
• Code：https://github.com/cszn/BSRGAN
• Tags: Blind SR

Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Wang_Unsupervised_Real-World_Super-Resolution_A_Domain_Adaptation_Perspective_ICCV_2021_paper.html
• Code(Unofficial): https://github.com/anse3832/USR_DA
• Tags: Unsupervised

Achieving On-Mobile Real-Time Super-Resolution With Neural Architecture and Pruning Search

• Paper: https://arxiv.org/abs/2108.08910

EvIntSR-Net: Event Guided Multiple Latent Frames Reconstruction and Super-Resolution

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Han_EvIntSR-Net_Event_Guided_Multiple_Latent_Frames_Reconstruction_and_Super-Resolution_ICCV_2021_paper.html
• Tags: Event

Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Li_Super-Resolving_Cross-Domain_Face_Miniatures_by_Peeking_at_One-Shot_Exemplar_ICCV_2021_paper.html

Dual-Camera Super-Resolution with Aligned Attention Modules

• Paper: https://arxiv.org/abs/2109.01349
• Code: https://github.com/Tengfei-Wang/DCSR
• Tags: Dual-Camera

Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts

• Paper：https://arxiv.org/abs/2104.06191
• Tags: Burst SR

Video Super Resolution

Deep Blind Video Super-resolution

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Pan_Deep_Blind_Video_Super-Resolution_ICCV_2021_paper.html
• Code：https://github.com/csbhr/Deep-Blind-VSR

Omniscient Video Super-Resolution

• Paper: https://arxiv.org/abs/2103.15683
• Code：https://github.com/psychopa4/OVSR

COMISR: Compression-Informed Video Super-Resolution

• Paper：https://arxiv.org/abs/2105.01237
• Code：https://github.com/google-research/google-research/tree/master/comisr

Real-World Video Super-Resolution: A Benchmark Dataset and a Decomposition Based Learning Scheme

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Yang_Real-World_Video_Super-Resolution_A_Benchmark_Dataset_and_a_Decomposition_Based_ICCV_2021_paper.html
• Code: https://github.com/IanYeung/RealVSR
• Tags: Real

Event Stream Super-Resolution via Spatiotemporal Constraint Learning

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Li_Event_Stream_Super-Resolution_via_Spatiotemporal_Constraint_Learning_ICCV_2021_paper.html
• Tags: Event

Image Rescaling - 图像缩放 [back]

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling

• Paper: https://arxiv.org/abs/2108.05301
• Code: https://github.com/JingyunLiang/HCFlow

Self-Conditioned Probabilistic Learning of Video Rescaling

• Paper: https://arxiv.org/abs/2107.11639
• Code: https://github.com/tianyuan168326/SelfC

Denoising - 去噪 [back]

Image Denoising

Rethinking Deep Image Prior for Denoising

• Paper: https://arxiv.org/abs/2108.12841
• Code: https://github.com/gistvision/DIP-denosing

Self-Supervised Image Prior Learning With GMM From a Single Noisy Image

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Liu_Self-Supervised_Image_Prior_Learning_With_GMM_From_a_Single_Noisy_ICCV_2021_paper.html
• Code：https://github.com/HUST-Tan/SS-GMM
• Tags: self-supervised, Gaussian Mixture Mode

Cross-Patch Graph Convolutional Network for Image Denoising

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Li_Cross-Patch_Graph_Convolutional_Network_for_Image_Denoising_ICCV_2021_paper.html
• Tags: GCN

C2N: Practical Generative Noise Modeling for Real-World Denoising

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Jang_C2N_Practical_Generative_Noise_Modeling_for_Real-World_Denoising_ICCV_2021_paper.html
• Code: https://github.com/onwn/c2n
• Tags: Noise Modeling

Rethinking Noise Synthesis and Modeling in Raw Denoising

• Paper: https://arxiv.org/abs/2110.04756
• Code: https://github.com/zhangyi-3/noise-synthesis
• Tags: Noise Modeling

Hyperspectral Image Denoising With Realistic Data

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Zhang_Hyperspectral_Image_Denoising_With_Realistic_Data_ICCV_2021_paper.html
• Code: https://github.com/ColinTaoZhang/HSIDwRD
• Tags: Hyperspectral Image

End-to-End Unsupervised Document Image Blind Denoising

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Gangeh_End-to-End_Unsupervised_Document_Image_Blind_Denoising_ICCV_2021_paper.html
• Tags: Unsupervised, Document Denoising

Video Denoising

Patch Craft: Video Denoising by Deep Modeling and Patch Matching

• Paper: https://arxiv.org/abs/2103.13767
• Code: https://github.com/grishavak/PaCNet-denoiser

Unsupervised Deep Video Denoising

• Paper: https://arxiv.org/abs/2011.15045
• Code: https://github.com/sreyas-mohan/udvd
• Tags: Unsupervised

Deblurring - 去模糊 [back]

Image Deblurring

Rethinking Coarse-to-Fine Approach in Single Image Deblurring

• Paper：https://arxiv.org/abs/2108.05054
• Code：https://github.com/chosj95/MIMO-UNet

Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions

• Paper：https://arxiv.org/abs/2108.09108
• Code: https://github.com/HyeongseokSon1/KPAC

Defocus Map Estimation and Deblurring From a Single Dual-Pixel Image

• Paper: https://arxiv.org/abs/2110.05655
• Code: https://github.com/cmu-ci-lab/dual_pixel_defocus_estimation_deblurring

Pyramid Architecture Search for Real-Time Image Deblurring

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Hu_Pyramid_Architecture_Search_for_Real-Time_Image_Deblurring_ICCV_2021_paper.html

Perceptual Variousness Motion Deblurring With Light Global Context Refinement

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Li_Perceptual_Variousness_Motion_Deblurring_With_Light_Global_Context_Refinement_ICCV_2021_paper.html

Motion Deblurring with Real Events

• Paper: https://arxiv.org/abs/2109.13695
• Code: https://github.com/xufangchn/Motion-Deblurring-with-Real-Events

Video Deblurring

Bringing Events into Video Deblurring with Non consecutively Blurry Frames

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Shang_Bringing_Events_Into_Video_Deblurring_With_Non-Consecutively_Blurry_Frames_ICCV_2021_paper.html
• Code：https://github.com/shangwei5/D2Net

Multi-Scale Separable Network for Ultra-High-Definition Video Deblurring

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Deng_Multi-Scale_Separable_Network_for_Ultra-High-Definition_Video_Deblurring_ICCV_2021_paper.html
• Code: https://github.com/dseny/UHDVD

Deraining - 去雨 [back]

Structure-Preserving Deraining with Residue Channel Prior Guidance

• Paper: https://arxiv.org/abs/2108.09079
• Code：https://github.com/Joyies/SPDNet

Improving De-Raining Generalization via Neural Reorganization

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Xiao_Improving_De-Raining_Generalization_via_Neural_Reorganization_ICCV_2021_paper.html
• Code：https://github.com/cszn/BSRGAN

Unpaired Learning for Deep Image Deraining With Rain Direction Regularizer

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Liu_Unpaired_Learning_for_Deep_Image_Deraining_With_Rain_Direction_Regularizer_ICCV_2021_paper.html

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

Unpaired Learning for High Dynamic Range Image Tone Mapping

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Vinker_Unpaired_Learning_for_High_Dynamic_Range_Image_Tone_Mapping_ICCV_2021_paper.html
• Code: https://github.com/yael-vinker/unpaired_hdr_tmo
• Tone Mapping

HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset

• Paper：https://arxiv.org/abs/2103.14943
• Code：https://github.com/guanyingc/DeepHDRVideo

A New Journey from SDRTV to HDRTV

• Paper：https://arxiv.org/abs/2108.07978
• Code：https://github.com/chxy95/HDRTVNet

**Ultra-High-Definition Image HDR Reconstruction via Collaborative Bilateral Learning **

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Zheng_Ultra-High-Definition_Image_HDR_Reconstruction_via_Collaborative_Bilateral_Learning_ICCV_2021_paper.html

Frame Interpolation - 插帧 [back]

XVFI: eXtreme Video Frame Interpolation

• Paper：https://arxiv.org/abs/2103.16206
• Code：https://github.com/JihyongOh/XVFI

Asymmetric Bilateral Motion Estimation for Video Frame Interpolation

• Paper： https://arxiv.org/abs/2108.06815
• Code： https://github.com/JunHeum/ABME

Training Weakly Supervised Video Frame Interpolation With Events

• Paper： https://openaccess.thecvf.com/content/ICCV2021/html/Yu_Training_Weakly_Supervised_Video_Frame_Interpolation_With_Events_ICCV_2021_paper.html

Motion-Aware Dynamic Architecture for Efficient Frame Interpolation

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Choi_Motion-Aware_Dynamic_Architecture_for_Efficient_Frame_Interpolation_ICCV_2021_paper.html

Image Enhancement - 图像增强 [back]

StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement

• Paper：https://arxiv.org/abs/2107.12898
• Code：https://github.com/IDKiro/StarEnhancer

Real-time Image Enhancer via Learnable Spatial-aware 3D Lookup Tables

• Paper：https://arxiv.org/abs/2108.08697

Deep Symmetric Network for Underexposed Image Enhancement With Recurrent Attentional Learning

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Zhao_Deep_Symmetric_Network_for_Underexposed_Image_Enhancement_With_Recurrent_Attentional_ICCV_2021_paper.html
• Code: https://github.com/lin-zhao-resoLve/Deep-Symmetric-Network-Enhancement

STAR: A Structure-Aware Lightweight Transformer for Real-Time Image Enhancement

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Zhang_STAR_A_Structure-Aware_Lightweight_Transformer_for_Real-Time_Image_Enhancement_ICCV_2021_paper.html
• Code: https://github.com/zzyfd/STAR-pytorch

Low-Light Image Enhancement

Adaptive Unfolding Total Variation Network for Low-Light Image Enhancement

• Paper：https://arxiv.org/abs/2110.00984
• Code：https://github.com/YU-Zhiyang/WEVI

Representative Color Transform for Image Enhancement

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Kim_Representative_Color_Transform_for_Image_Enhancement_ICCV_2021_paper.html
• Code: https://github.com/ThanosM97/Representative-Color-Transform

Seeing Dynamic Scene in the Dark: A High-Quality Video Dataset With Mechatronic Alignment

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Wang_Seeing_Dynamic_Scene_in_the_Dark_A_High-Quality_Video_Dataset_ICCV_2021_paper.html
• Code: https://github.com/dvlab-research/SDSD

Image Harmonization/Composition - 图像协调/图像合成 [back]

SSH: A Self-Supervised Framework for Image Harmonization

• Paper：https://arxiv.org/abs/2108.06805
• Code：https://github.com/VITA-Group/SSHarmonization

Image Harmonization With Transformer

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Guo_Image_Harmonization_With_Transformer_ICCV_2021_paper.html
• Code: https://github.com/zhenglab/HarmonyTransformer

Image Completion/Inpainting - 图像修复 [back]

High-Fidelity Pluralistic Image Completion with Transformers

• Paper：https://arxiv.org/abs/2103.14031
• Code：https://github.com/raywzy/ICT

Image Inpainting via Conditional Texture and Structure Dual Generation

• Paper：https://arxiv.org/abs/2108.09760
• Code：https://github.com/Xiefan-Guo/CTSDG

CR-Fill: Generative Image Inpainting with Auxiliary Contextual Reconstruction

• Paper：https://arxiv.org/abs/2011.12836
• Code：https://github.com/zengxianyu/crfill

Parallel Multi-Resolution Fusion Network for Image Inpainting

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Wang_Parallel_Multi-Resolution_Fusion_Network_for_Image_Inpainting_ICCV_2021_paper.html

WaveFill: A Wavelet-based Generation Network for Image Inpainting

• Paper: https://arxiv.org/abs/2107.11027
• Code: https://github.com/yingchen001/WaveFill

Learning a Sketch Tensor Space for Image Inpainting of Man-made Scenes

• Paper: https://arxiv.org/abs/2103.15087
• Code: https://github.com/ewrfcas/MST_inpainting

Distillation-Guided Image Inpainting

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Suin_Distillation-Guided_Image_Inpainting_ICCV_2021_paper.html

Video Inpainting

Internal Video Inpainting by Implicit Long-range Propagation

• Paper: https://arxiv.org/abs/2108.01912
• Code1：https://github.com/Tengfei-Wang/Annotated-4K-Videos
• Code2: https://github.com/Tengfei-Wang/Implicit-Internal-Video-Inpainting

Occlusion-Aware Video Object Inpainting

• Paper：https://arxiv.org/abs/2108.06765

FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Liu_FuseFormer_Fusing_Fine-Grained_Information_in_Transformers_for_Video_Inpainting_ICCV_2021_paper.html
• Code：https://github.com/ruiliu-ai/FuseFormer

Flow-Guided Video Inpainting with Scene Templates

• Paper: https://arxiv.org/abs/2108.12845
• Code: https://github.com/donglao/videoinpainting

Image Matting - 图像抠图 [back]

Cascade Image Matting with Deformable Graph Refinement

• Paper: https://arxiv.org/abs/2105.02646

Tripartite Information Mining and Integration for Image Matting

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Liu_Tripartite_Information_Mining_and_Integration_for_Image_Matting_ICCV_2021_paper.html
• Code: https://github.com/kelisiya/TIMI-Net

Virtual Multi-Modality Self-Supervised Foreground Matting for Human-Object Interaction

• Paper: https://arxiv.org/abs/2110.03278
• Code: https://github.com/jacksyu/hoi-matting

Video Matting via Consistency-Regularized Graph Neural Networks

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Wang_Video_Matting_via_Consistency-Regularized_Graph_Neural_Networks_ICCV_2021_paper.html
• Code: https://github.com/TiantianWang/VideoMatting-CRGNN

Image Stitching - 图像拼接 [back]

Minimal Solutions for Panoramic Stitching Given Gravity Prior

• Paper: https://arxiv.org/abs/2012.00465

Image Compression - 图像压缩 [back]

Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform

• Paper：https://arxiv.org/abs/2108.09551
• Code：https://github.com/micmic123/QmapCompression

Neural Image Compression via Attentional Multi-Scale Back Projection and Frequency Decomposition

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Gao_Neural_Image_Compression_via_Attentional_Multi-Scale_Back_Projection_and_Frequency_ICCV_2021_paper.html

Video Compression

Extending Neural P-frame Codecs for B-frame Coding

• Paper：https://arxiv.org/abs/2104.00531

Efficient Video Compression via Content-Adaptive Super-Resolution

• Paper：https://arxiv.org/abs/2104.02322
• Code：https://github.com/AdaptiveVC/SRVC

Online-Trained Upsampler for Deep Low Complexity Video Compression

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Klopp_Online-Trained_Upsampler_for_Deep_Low_Complexity_Video_Compression_ICCV_2021_paper.html

Image Quality Assessment - 图像质量评价 [back]

Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

• Paper: https://arxiv.org/abs/2108.07948
• Code: https://github.com/researchmm/CKDN

Unsupervised Curriculum Domain Adaptation for No-Reference Video Quality Assessment

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Chen_Unsupervised_Curriculum_Domain_Adaptation_for_No-Reference_Video_Quality_Assessment_ICCV_2021_paper.html
• Code: https://github.com/cpf0079/UCDA

MUSIQ: Multi-scale Image Quality Transformer

• Paper: https://arxiv.org/abs/2108.05997
• Code: https://github.com/anse3832/MUSIQ

Style Transfer - 风格迁移 [back]

Diverse Image Style Transfer via Invertible Cross-Space Mapping

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Chen_Diverse_Image_Style_Transfer_via_Invertible_Cross-Space_Mapping_ICCV_2021_paper.html

DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Xu_DRB-GAN_A_Dynamic_ResBlock_Generative_Adversarial_Network_for_Artistic_Style_ICCV_2021_paper.html

Domain Aware Universal Style Transfer

• Paper：https://arxiv.org/abs/2108.04441
• Code：https://github.com/Kibeom-Hong/Domain-Aware-Style-Transfer

StyleFormer: Real-Time Arbitrary Style Transfer via Parametric Style Composition

• Paper：https://openaccess.thecvf.com/content/ICCV2021/html/Wu_StyleFormer_Real-Time_Arbitrary_Style_Transfer_via_Parametric_Style_Composition_ICCV_2021_paper.html

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

• Paper：https://arxiv.org/abs/2108.03647
• Code：https://github.com/Huage001/AdaAttN

Manifold Alignment for Semantically Aligned Style Transfer

• Paper: https://arxiv.org/abs/2005.10777
• Code: https://github.com/NJUHuoJing/MAST

ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity

• Paper：https://arxiv.org/abs/2103.09776

Image Editing - 图像编辑 [back]

Latent Transformations via NeuralODEs for GAN-Based Image Editing

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Khrulkov_Latent_Transformations_via_NeuralODEs_for_GAN-Based_Image_Editing_ICCV_2021_paper.html

Language-Guided Global Image Editing via Cross-Modal Cyclic Mechanism

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Jiang_Language-Guided_Global_Image_Editing_via_Cross-Modal_Cyclic_Mechanism_ICCV_2021_paper.html

Talk-to-Edit: Fine-Grained Facial Editing via Dialog

• Paper: https://arxiv.org/abs/2109.04425
• Code: https://github.com/yumingj/Talk-to-Edit

A Latent Transformer for Disentangled Face Editing in Images and Videos

• Paper: https://arxiv.org/abs/2106.11895
• Code: https://github.com/InterDigitalInc/latent-transformer

GAN Inversion for Out-of-Range Images with Geometric Transformations

• Paper: https://arxiv.org/abs/2108.08998
• Code: https://github.com/kkang831/BDInvert_Release

Image Shape Manipulation from a Single Augmented Training Sample

• Paper: https://arxiv.org/abs/2007.01289
• Code: https://github.com/eliahuhorwitz/DeepSIM

Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing

• Paper: https://arxiv.org/abs/2104.07021
• Code: https://github.com/cuiaiyu/dressing-in-order

Toward a Visual Concept Vocabulary for GAN Latent Space

• Paper: https://arxiv.org/abs/2110.04292
• Code: https://github.com/schwettmann/visual-vocab

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

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

StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery

• Paper: https://arxiv.org/abs/2103.17249
• Code: https://github.com/orpatashnik/StyleCLIP

DAE-GAN: Dynamic Aspect-Aware GAN for Text-to-Image Synthesis

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Ruan_DAE-GAN_Dynamic_Aspect-Aware_GAN_for_Text-to-Image_Synthesis_ICCV_2021_paper.html
• Code: https://github.com/hiarsal/DAE-GAN

PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering

• Paper: https://arxiv.org/abs/2109.08379
• Code: https://github.com/RenYurui/PIRender

Image-to-Image / Image Guided

Bridging the Gap Between Label- and Reference-Based Synthesis in Multi-Attribute Image-to-Image Translation

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Huang_Bridging_the_Gap_Between_Label-_and_Reference-Based_Synthesis_in_Multi-Attribute_ICCV_2021_paper.html
• Code: https://github.com/huangqiusheng/BridgeGAN

Instance-wise Hard Negative Example Generation for Contrastive Learning in Unpaired Image-to-Image Translation

• Paper: https://arxiv.org/abs/2108.04547
• Code: https://github.com/WeilunWang/NEGCUT

Unaligned Image-to-Image Translation by Learning to Reweight

• Paper：https://arxiv.org/abs/2109.11736
• Code：https://github.com/Mid-Push/IrwGAN

TransferI2I: Transfer Learning for Image-to-Image Translation from Small Datasets

• Paper: https://arxiv.org/abs/2105.06219

SPatchGAN: A Statistical Feature Based Discriminator for Unsupervised Image-to-Image Translation

• Paper：https://arxiv.org/abs/2103.16219
• Code：https://github.com/NetEase-GameAI/SPatchGAN

Rethinking the Truly Unsupervised Image-to-Image Translation

• Paper: https://arxiv.org/abs/2006.06500
• Code: https://github.com/clovaai/tunit

Scaling-up Disentanglement for Image Translation

• Paper：https://arxiv.org/abs/2103.14017
• Code：https://github.com/avivga/overlord

Harnessing the Conditioning Sensorium for Improved Image Translation

• Paper: https://arxiv.org/abs/2110.06443

Semantically Robust Unpaired Image Translation for Data with Unmatched Semantics Statistics

• Paper: https://arxiv.org/abs/2012.04932
• Code: https://github.com/SeanJia/SRUNIT

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving

• Paper: https://arxiv.org/abs/2011.13611
• Code: https://github.com/mu-cai/frequency-domain-image-translation

Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Translation

• Paper: https://arxiv.org/abs/2103.16146
• Code: https://github.com/cyclomon/DiagonalGAN

Image Synthesis via Semantic Composition

• Paper: https://arxiv.org/abs/2109.07053
• Code:https://github.com/dvlab-research/SCGAN

Collaging Class-specific GANs for Semantic Image Synthesis

• Paper: https://arxiv.org/abs/2110.04281

Image Synthesis From Layout With Locality-Aware Mask Adaption

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Li_Image_Synthesis_From_Layout_With_Locality-Aware_Mask_Adaption_ICCV_2021_paper.html

Structure-Transformed Texture-Enhanced Network for Person Image Synthesis

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Xu_Structure-Transformed_Texture-Enhanced_Network_for_Person_Image_Synthesis_ICCV_2021_paper.html

ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models

• Paper: https://arxiv.org/abs/2108.02938
• Code: https://github.com/jychoi118/ilvr_adm

Sketch Your Own GAN

• Paper: https://arxiv.org/abs/2108.02774
• Code: https://github.com/PeterWang512/GANSketching

Re-Aging GAN: Toward Personalized Face Age Transformation

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Makhmudkhujaev_Re-Aging_GAN_Toward_Personalized_Face_Age_Transformation_ICCV_2021_paper.html

Others for image generation

Focal Frequency Loss for Image Reconstruction and Synthesis

• Paper: https://arxiv.org/abs/2012.12821
• Code: https://github.com/EndlessSora/focal-frequency-loss

Unsupervised Image Generation with Infinite Generative Adversarial Networks

• Paper: https://arxiv.org/abs/2108.07975
• Code: https://github.com/yinghdb/MICGANs

Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Chen_Semi-Supervised_Single-Stage_Controllable_GANs_for_Conditional_Fine-Grained_Image_Generation_ICCV_2021_paper.html

Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation

• Paper: https://arxiv.org/abs/2108.07668
• Code: https://github.com/csyxwei/OroJaR

LoFGAN: Fusing Local Representations for Few-Shot Image Generation

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Gu_LoFGAN_Fusing_Local_Representations_for_Few-Shot_Image_Generation_ICCV_2021_paper.html
• Code: https://github.com/edward3862/LoFGAN-pytorch

Dual Projection Generative Adversarial Networks for Conditional Image Generation

• Paper: https://arxiv.org/abs/2108.09016
• Code: https://github.com/phymhan/P2GAN

Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation

• Paper: https://arxiv.org/abs/2103.16795
• Code: https://github.com/boschresearch/MCCGAN

GAN-Control: Explicitly Controllable GANs

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Shoshan_GAN-Control_Explicitly_Controllable_GANs_ICCV_2021_paper.html
• Code: https://github.com/amazon-science/gan-control

Omni-GAN: On the Secrets of cGANs and Beyond

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Zhou_Omni-GAN_On_the_Secrets_of_cGANs_and_Beyond_ICCV_2021_paper.html
• Code: https://github.com/PeterouZh/Omni-GAN-PyTorch

Detail Me More: Improving GAN's Photo-Realism of Complex Scenes

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Gadde_Detail_Me_More_Improving_GANs_Photo-Realism_of_Complex_Scenes_ICCV_2021_paper.html

Online Multi-Granularity Distillation for GAN Compression

• Paper: https://arxiv.org/abs/2108.06908
• Code: https://github.com/bytedance/OMGD

WarpedGANSpace: Finding non-linear RBF paths in GAN latent space

• Paper: https://arxiv.org/abs/2109.13357
• Code: https://github.com/chi0tzp/WarpedGANSpace

Video Generation

Click to Move: Controlling Video Generation with Sparse Motion

• Paper: https://arxiv.org/abs/2108.08815
• Code: https://github.com/PierfrancescoArdino/C2M

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis

• Paper: https://arxiv.org/abs/2107.02790
• Code: https://github.com/CompVis/ipoke

Sat2Vid: Street-view Panoramic Video Synthesis from a Single Satellite Image

• Paper: https://arxiv.org/abs/2012.06628

Others [back]

Neural Video Portrait Relighting in Real-time via Consistency Modeling

• Paper: https://arxiv.org/abs/2104.00484
• Code: https://github.com/ZoneLikeWonderland/Neural-Video-Portrait-Relighting-in-Real-time-via-Consistency-Modeling
• Tags: Relighting

Towards Vivid and Diverse Image Colorization with Generative Color Prior

• Paper：https://arxiv.org/abs/2108.08826
• Code: https://github.com/ToTheBeginning/GCP-Colorization
• Tags: Colorization

Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects

• Paper：https://arxiv.org/abs/2107.01619
• Code: https://github.com/niceDuckgu/CDR
• Tags: Colorization

Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation

• Paper: https://arxiv.org/abs/2108.08202
• Code: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021
• Tags: Video Delivery

IICNet: A Generic Framework for Reversible Image Conversion

• Paper: https://arxiv.org/abs/2109.04242
• Code: https://github.com/felixcheng97/IICNet
• Tags: Reversible Image Conversion

FashionMirror: Co-Attention Feature-Remapping Virtual Try-On With Sequential Template Poses

• Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Chen_FashionMirror_Co-Attention_Feature-Remapping_Virtual_Try-On_With_Sequential_Template_Poses_ICCV_2021_paper.html
• Code: https://github.com/FashionMirror/FashionMirror
• Tags: Virtual Try-on

Talking Head Generation

Learned Spatial Representations for Few-shot Talking-Head Synthesis

• Paper: https://arxiv.org/abs/2104.14557
• Code: https://github.com/MoustafaMeshry/lsr

FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning

• Paper: https://arxiv.org/abs/2108.07938
• Code: https://github.com/zhangchenxu528/FACIAL

Handwriting/Font Generation

Handwriting Transformers

• Paper: https://arxiv.org/abs/2104.03964
• Code: https://github.com/ankanbhunia/Handwriting-Transformers

Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Exper

• Paper: https://arxiv.org/abs/2104.00887
• Code: https://github.com/clovaai/mxfont