# Awesome-GAN-based-Image-Restoration **Repository Path**: Heconnor/Awesome-GAN-based-Image-Restoration ## Basic Information - **Project Name**: Awesome-GAN-based-Image-Restoration - **Description**: No description available - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: Ly123n-patch-1 - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2024-08-26 - **Last Updated**: 2024-08-26 ## Categories & Tags **Categories**: Uncategorized **Tags**: ImageRestoration, AwesomeNote, GenerativeAdversarialNetworks ## README # Awesome-GAN-based-Image-Restoration Awesome GAN-based Image Restoration ## 2008 ### Super-Resolution (**CVPR 08**) Image Super-Resolution using Gradient Profile Prior [[paper](https://ieeexplore.ieee.org/document/4587659)][[code](https://github.com/changruowang/SR_GPP)] ## 2015 ### Super-Resolution (**TIP 15**) Single Image Superresolution Based on Gradient Profile Sharpness [[paper](https://ieeexplore.ieee.org/document/7063909)][[code](https://github.com/Hesam-lab/Image-Super-resolution)] (**CVPR 15**) Single Image Super-resolution from Transformed Self-Exemplars [[paper](https://vision.ai.illinois.edu/html-files-to-import/publications/huangcvpr2015.pdf)][[code](https://github.com/jbhuang0604/SelfExSR)] ## 2017 ### Denosing (**ICIP 17**) Estimation of signal-dependent noise level function using multi-column convolutional neural network [[paper](https://ieeexplore.ieee.org/abstract/document/8296716)] ### Super-Resolution (**MICCAI 17**) Image Super Resolution Using Generative Adversarial Networks and Local Saliency Maps for Retinal Image Analysis [[paper](https://arxiv.org/pdf/1710.04783.pdf)][[code](https://github.com/qinenergy/cotta)] (**CVPR 17**) Image-to-Image Translation with Conditional Adversarial Networks [[paper](https://arxiv.org/pdf/1611.07004.pdf)][[code](https://github.com/phillipi/pix2pix)] ### Deblurring (**CVPR 17**) Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network [[paper](https://arxiv.org/pdf/1609.04802.pdf)][[code](https://github.com/tensorlayer/srgan)] (**CVPR 17**) Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring [[paper](https://openaccess.thecvf.com/content_cvpr_2017/papers/Nah_Deep_Multi-Scale_Convolutional_CVPR_2017_paper.pdf)][[code](https://github.com/SeungjunNah/DeepDeblur_release)] ## 2018 ### Super-Resolution (**CVPRW 18**) Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networks [[paper](https://arxiv.org/pdf/1809.00437.pdf)][[code](https://github.com/Junshk/CinCGAN-pytorch)] (**ICASSP 18**) Joint License Plate Super-Resolution and Recognition in One Multi-Task Gan Framework [[paper](https://ieeexplore.ieee.org/document/8462282)][[code](https://github.com/Junshk/CinCGAN-pytorch)] ### Denosing (**ICASSP 18**) Image Restoration with Deep Generative Models [[paper](https://sci-hub.se/10.1109/icassp.2018.8462317)] (**CVPR 18**) Image Blind Denoising With Generative Adversarial Network Based Noise Modeling [[paper](https://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Image_Blind_Denoising_CVPR_2018_paper.pdf)] (**CISP-BMEI 18**) Generative Adversarial Networks with Dense Connection for Optical Coherence Tomography Images Denoising [[paper](https://sci-hub.se/10.1109/cisp-bmei.2018.8633086)] (**ArXiv 18**) Correction by Projection: Denoising Images with Generative Adversarial Networks [[paper](https://arxiv.org/pdf/1803.04477.pdf)] (**ICSM 18**) Adversarial Training for Dual-Stage Image Denoising Enhanced with Feature Matching [[paper](https://www.sci-hub.se/10.1007/978-3-030-04375-9_30)] (**IPTA 18**) A new generative adversarial network for texture preserving image denoising [[paper](https://www.bothonce.com/10.1109/ipta.2018.8608126)] (**BOE 18**) Speckle noise reduction in optical coherence tomography images based on edge-sensitive cGAN [[paper](https://www.bothonce.com/10.1364/boe.9.005129)] ### Dehazing (**AAAI 18**) Towards perceptual image dehazing by physics-based disentanglement and adversarial training [[paper](https://dl.acm.org/doi/pdf/10.5555/3504035.3504952)] (**IJCAI 18**) DehazeGAN: When Image Dehazing Meets Differential Programming [[paper](https://www.ijcai.org/proceedings/2018/0172.pdf)] (**CVPR 18**) Gated Fusion Network for Single Image Dehazing [[paper](https://arxiv.org/pdf/1804.00213v1.pdf)][[code](https://github.com/rwenqi/GFN-dehazing)] (**CVPR 18**) Single Image Dehazing via Conditional Generative Adversarial Network [[paper](https://openaccess.thecvf.com/content_cvpr_2018/html/Li_Single_Image_Dehazing_CVPR_2018_paper.html)] (**CVPR 18**) Cycle-dehaze: Enhanced CycleGAN for single image dehazing [[paper](https://arxiv.org/pdf/1805.05308.pdf)][[code](https://github.com/engindeniz/Cycle-Dehaze)] (**CVPR 18**) Densely Connected Pyramid Dehazing Network [[paper](https://arxiv.org/pdf/1803.08396.pdf)][[code](https://github.com/hezhangsprinter/DCPDN)] ### Dwraining (**CVPR 18**) Attentive Generative Adversarial Network for Raindrop Removal from A Single Image [[paper](https://arxiv.org/pdf/1711.10098.pdf)][[code](https://github.com/rui1996/DeRaindrop)] ### Deblurring (**CVPR 18**) Deep Semantic Face Deblurring [[paper](https://arxiv.org/pdf/1803.03345.pdf)][[code](https://github.com/joanshen0508/Deep-Semantic-Face-Deblurring)] (**CVPR 18**) DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks [[paper](https://openaccess.thecvf.com/content_cvpr_2018/papers/Kupyn_DeblurGAN_Blind_Motion_CVPR_2018_paper.pdf)] (**ECCV 18**) Unsupervised class-specific deblurring [[paper](https://openaccess.thecvf.com/content_ECCV_2018/papers/Nimisha_T_M_Unsupervised_Class-Specific_Deblurring_ECCV_2018_paper.pdf)] (**TIP 18**) Adversarial Spatio-Temporal Learning for Video Deblurring [[paper](https://arxiv.org/pdf/1804.00533.pdf)][[code](https://github.com/JLtwoP/Adversarial-Spatio-Temporal-Learning-for-Video-Deblurring)] ## 2019 ### Super-Resolution (**ICCV 19**) RankSRGAN: Generative Adversarial Networks With Ranker for Image Super-Resolution [[paper](https://arxiv.org/pdf/2107.09427.pdf)][[code](https://github.com/XPixelGroup/RankSRGAN)] (**ICCV 19**) Kernel Modeling Super-Resolution on Real Low-Resolution Images [[paper](https://openaccess.thecvf.com/content_ICCV_2019/papers/Zhou_Kernel_Modeling_Super-Resolution_on_Real_Low-Resolution_Images_ICCV_2019_paper.pdf)][[code](https://github.com/IVRL/Kernel-Modeling-Super-Resolution)] (**IEEE TIP 19**) Multiple Cycle-in-Cycle Generative Adversarial Networks for Unsupervised Image Super-Resolution [[paper](https://ieeexplore.ieee.org/abstract/document/8825849)][[code](https://github.com/XPixelGroup/RankSRGAN)] (**IEEE TMI 19**) CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE) [[paper](https://arxiv.org/pdf/1808.04256.pdf)][[code](https://github.com/charlesyou999648/GAN-CIRCLE)] ### Denosing (**ArXiv 19**) Unsupervised Image Noise Modeling with Self-Consistent GAN [[paper](https://arxiv.org/pdf/1906.05762.pdf)] (**CVPRW 19**) Real Photographs Denoising With Noise Domain Adaptation and Attentive Generative Adversarial Network [[paper](https://openaccess.thecvf.com/content_CVPRW_2019/papers/NTIRE/Lin_Real_Photographs_Denoising_With_Noise_Domain_Adaptation_and_Attentive_Generative_CVPRW_2019_paper.pdf)] (**ICICT 19**) Image Denoising Using A Generative Adversarial Network [[paper](https://www.evl.uic.edu/documents/aalsaiari_ieee2019_imagedenoising.pdf)] (**Computers in Biology and Medicine 19**) Three-dimensional optical coherence tomography image denoising through multi-input fully-convolutional networks [[paper](https://arxiv.org/ftp/arxiv/papers/1811/1811.09022.pdf)] ### Dehazing (**EAAI 19**) DD-CycleGAN: Unpaired image dehazing via Double-Discriminator Cycle-Consistent Generative Adversarial Network [[paper](https://www.bothonce.com/10.1016/j.engappai.2019.04.003)] (**WACV 19**) CDNet: Single Image De-Hazing Using Unpaired Adversarial Training [[paper](https://sci-hub.se/10.1109/wacv.2019.00127)] (**CVPR 19**) Enhanced pix2pix dehazing network [[paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Qu_Enhanced_Pix2pix_Dehazing_Network_CVPR_2019_paper.pdf)][[code](https://github.com/ErinChen1/EPDN)] ### Deblurring (**CVPR 19**) Unsupervised Domain-Specific Deblurring via Disentangled Representations [[paper](https://arxiv.org/pdf/1903.01594.pdf)][[code](https://github.com/ustclby/Unsupervised-Domain-Specific-Deblurring/)] (**ICCV 19**) DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better [[paper](https://arxiv.org/pdf/1908.03826.pdf)][[code](https://github.com/VITA-Group/DeblurGANv2)] ### Deraining (**CVPR 19**) Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning [[paper](https://arxiv.org/pdf/1904.05050.pdf)][[code](https://github.com/liruoteng/HeavyRainRemoval)] (**ArXiv 19**) Gradient Information Guided Deraining with A Novel Network and Adversarial Training [[paper](https://arxiv.org/pdf/1910.03839.pdf)] (**ICIP 19**) Unsupervised Single Image Deraining with Self-supervised Constraints [[paper](https://arxiv.org/pdf/1811.08575.pdf)] (**ICCV 19**) Deep Learning for Seeing Through Window With Raindrops [[paper](https://openaccess.thecvf.com/content_ICCV_2019/html/Quan_Deep_Learning_for_Seeing_Through_Window_With_Raindrops_ICCV_2019_paper.html)][[code](https://github.com/ljm619/raindropAttention)] (**AAAI 19**) Singe image rain removal with unpaired information: a differentiable programming perspective [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/4971/4844)] (**ACM MM 19**) DTDN: Dual-task De-raining Network [[paper](https://arxiv.org/pdf/2008.09326.pdf)][[code](https://github.com/long-username/DTDN-DTDN-Dual-task-De-raining-Network)] ### Desnowing (**Access 19**) Single Image Snow Removal via Composition Generative Adversarial Networks [[paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8645630)] ## 2020 ### Super-Resolution (**IEEE TMI 20**) PathSRGAN: Multi-supervised super-resolution for cytopathological images using generative adversarial network [[paper](https://ieeexplore.ieee.org/document/9036984)][[code](https://github.com/majiabo/PathSRGAN)] (**CVPR 20**) Unsupervised Real Image Super-Resolution via Generative Variational AutoEncoder [[paper](https://arxiv.org/pdf/2004.12811.pdf)][[code](https://github.com/Holmes-Alan/dSRVAE)] (**CVPR 20**) Perceptual Extreme Super Resolution Network with Receptive Field Block [[paper](https://arxiv.org/pdf/2005.12597.pdf)][[code](https://github.com/Lornatang/RFB_ESRGAN-PyTorch)] (**IEEE TMM 20**) Supervised Pixel-Wise GAN for Face Super-Resolution [[paper](https://ieeexplore.ieee.org/document/9132630)][[code](https://github.com/Merle314/Supervised-Pixel-Wise-GAN)] (**CVPR 20**) Unpaired Image Super-Resolution using Pseudo-Supervision [[paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Maeda_Unpaired_Image_Super-Resolution_Using_Pseudo-Supervision_CVPR_2020_paper.pdf)][[code](https://github.com/jkhu29/UnpairedSR)] (**CVPRW 20**) Unsupervised Real-World Super Resolution With Cycle Generative Adversarial Network and Domain Discriminator [[paper](https://openaccess.thecvf.com/content_CVPRW_2020/html/w31/Kim_Unsupervised_Real-World_Super_Resolution_With_Cycle_Generative_Adversarial_Network_and_CVPRW_2020_paper.html)][[code](https://github.com/GT-KIM/unsupervised-super-resolution-domain-discriminator)] ### Dehazing (**CVPR 20**) Domain Adaptation for Image Dehazing [[paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Shao_Domain_Adaptation_for_Image_Dehazing_CVPR_2020_paper.pdf)][[code](https://github.com/HUSTSYJ/DA_dahazing)] (**TIP 20**) Deep dehazing network with latent ensembling architecture and adversarial learning [[paper](https://sci-hub.se/10.1109/tip.2020.3044208)] (**TIP 20**) End to-end single image fog removal using enhanced cycle consistent adversarial networks [[paper](https://arxiv.org/pdf/1902.01374v1.pdf)] (**TIP 20**) Fusion of Heterogeneous Adversarial Networks for Single Image Dehazing [[paper](https://ieeexplore.ieee.org/document/9018375)] (**ICIP 20**) Unsupervised Conditional Disentangle Network For Image Dehazing [[paper](https://arxiv.org/pdf/2107.06681.pdf)] ### Deraining (**Mathematics 20**) Selective generative adversarial network for raindrop removal from a single image [[paper](https://www.semanticscholar.org/reader/384f8f42c1e01401421082c1cb38541c4fd882cf)] ### Desnowing (**ECCV 20**) JSTASR: Joint Size and Transparency-AwareSnow Removal Algorithm Based on ModifiedPartial Convolution and Veiling Effect Removal [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123660749.pdf)][[code](https://github.com/weitingchen83/JSTASR-DesnowNet-ECCV-2020)] (**TCSVT 20**) DesnowGAN: An Efficient Single Image Snow Removal Framework Using Cross-Resolution Lateral Connection and GANs [[paper](https://sci-hub.se/10.1109/tcsvt.2020.3003025)] ## 2021 ### Super-Resolution (**ICCV 21**) Fourier Space Losses for Efficient Perceptual Image Super-Resolution [[paper](https://arxiv.org/pdf/2106.00783.pdf)][[code](https://github.com/qinenergy/cotta)] (**ICCV 21**) Focal Frequency Loss for Image Reconstruction and Synthesis [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Jiang_Focal_Frequency_Loss_for_Image_Reconstruction_and_Synthesis_ICCV_2021_paper.pdf)][[code](https://github.com/EndlessSora/focal-frequency-loss)] (**CVPR 21**) GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution [[paper](https://arxiv.org/pdf/2012.00739.pdf)][[code](https://github.com/ckkelvinchan/GLEAN)] ### Deraining (**TIP 21**) DerainCycleGAN: Rain Attentive CycleGAN for Single Image Deraining and Rainmaking [[paper](https://arxiv.org/ftp/arxiv/papers/1912/1912.07015.pdf)][[code](https://github.com/OaDsis/DerainCycleGAN/blob/main/README.md)] (**TCSVT 21**) Image De-raining Using a Conditional Generative Adversarial Network [[paper](https://arxiv.org/pdf/1701.05957.pdf)][[code](https://github.com/hezhangsprinter/ID-CGAN)] (**ICME 21**) Semi-Deraingan: A New Semi-Supervised Single Image Deraining [[paper](https://arxiv.org/ftp/arxiv/papers/2001/2001.08388.pdf)] (**Mathematical Problems in Engineering 21**) Research of Single Image Rain Removal Algorithm Based on LBP-CGAN Rain Generation Method [[paper](https://www.hindawi.com/journals/mpe/2021/8865843/)] (**CVPR 21**) Closing the loop: joint rain generation and removal via disentangled image translation [[paper](https://arxiv.org/pdf/2103.13660.pdf)][[code](https://github.com/guyii54/JRGR)] (**CVPR 21**) Controlling the Rain: From Removal to Rendering [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Ni_Controlling_the_Rain_From_Removal_to_Rendering_CVPR_2021_paper.pdf)] ### Dehazing (**Signal Processing: Image Communication 21**) A GAN-Based Input-Size Flexibility Model for Single Image Dehazing [[paper](https://arxiv.org/pdf/2102.09796.pdf)] (**TIP 21**) RefineDNet: A weakly supervised refinement framework for single image dehazing [[paper](https://www.bothonce.com/10.1109/tip.2021.3060873)][[code](https://github.com/xiaofeng94/RefineDNet-for-dehazing)] (**CVPRW 21**) DW-GAN: A Discrete Wavelet Transform GAN for NonHomogeneous Dehazing [[paper](https://arxiv.org/pdf/2104.08911.pdf)][[code](https://github.com/liuh127/NTIRE-2021-Dehazing-DWGAN)] (**TCSVT 21**) TMS-GAN: A Twofold Multi-Scale Generative Adversarial Network for Single Image Dehazing [[paper](https://ieeexplore.ieee.org/document/9489298)] ### Desnowing (**ACCESS 21**) Single-Image Snow Removal Based on an Attention Mechanism and a Generative Adversarial Network [[paper](https://sci-hub.se/10.1109/access.2021.3051359)] (**IET Computer Vision 21**) Single-Image Snow Removal Based on an Attention Mechanism and a Generative Adversarial Network [[paper](https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cvi2.12038)] ## 2022 ### Dehazing (**TMM 22**) USID-Net: Unsupervised single image dehazing network via disentangled representations [[paper](https://ieeexplore.ieee.org/abstract/document/9745359)][[code](https://github.com/dehazing/USID-Net)] (**CVPR 22**) Self-Augmented Unpaired Image Dehazing via Density and Depth Decomposition [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Yang_Self-Augmented_Unpaired_Image_Dehazing_via_Density_and_Depth_Decomposition_CVPR_2022_paper.pdf)][[code](https://github.com/YaN9-Y/D4)] (**JIVCIR 22**) DCA-CycleGAN: Unsupervised single image dehazing using Dark Channel Attention optimized CycleGAN [[paper](https://dlnext.acm.org/doi/10.1016/j.jvcir.2021.103431)] ### Desnowing (**Social Science Research 22**) Sequential Dual Generative Adversarial Network for Snow and Haze Elimination [[paper](https://www.semanticscholar.org/paper/Sequential-Dual-Generative-Adversarial-Network-for-Bao-Qiang/14857e5c3dae5052de2101b088cd1d440e8a1dab)] ## 2023 ### Super-Resolution (**CVPR 23**) Super-scale your images and run experiments with Residual Dense and Adversarial Networks [[paper](https://arxiv.org/pdf/2303.14726.pdf)][[code](https://github.com/csxmli2016/MARCONet)] ### Desnowing (**IET 23**) Single-Image Snow Removal Based on an Attention Mechanism and a Generative Adversarial Network [[paper](https://www.researchgate.net/publication/348697758_Single-Image_Snow_Removal_Based_on_an_Attention_Mechanism_and_a_Generative_Adversarial_Network)]