Awesome

[🔥] A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trends

Junjun Jiang, Zengyuan Zuo,Gang Wu, Kui Jiang and Xianming Liu

AIIA Lab, Harbin Institute of Technology.

Overview

News

• 🚀 Our comprehensive survey paper on All-in-One Image Restoration has been released. We are actively developing this project and will provide regular updates to reflect the latest advancements in the field.

Awesome All-in-one Image Restoration Paper List

2024

[TIP]MWFormer: Multi-Weather Image Restoration Using Degradation-Aware Transformers

Ruoxi Zhu, Zhengzhong Tu, Jiaming Liu, Alan C. Bovik, Yibo Fan

• Paper: https://arxiv.org/abs/2411.17226
• Code: https://github.com/taco-group/MWFormer

[Arxiv]FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration

Hao Li, Xiang Chen, Jiangxin Dong, Jinhui Tang, Jinshan Pan

• Paper: https://arxiv.org/abs/2412.01427

[Arxiv]Complexity Experts are Task-Discriminative Learners for Any Image Restoration

Eduard Zamfir, Zongwei Wu, Nancy Mehta, Yuedong Tan, Danda Pani Paudel, Yulun Zhang, Radu Timofte

• Paper: https://arxiv.org/abs/2411.18466
• Code: https://github.com/eduardzamfir/MoCE-IR

[Arxiv]Adaptive Blind All-in-One Image Restoration

David Serrano-Lozano, Luis Herranz, Shaolin Su, Javier Vazquez-Corral

• Paper: https://arxiv.org/abs/2411.18412
• Code: https://github.com/davidserra9/abair/

[Arxiv]GenDeg: Diffusion-Based Degradation Synthesis for Generalizable All-in-One Image Restoration

Sudarshan Rajagopalan, Nithin Gopalakrishnan Nair, Jay N. Paranjape, Vishal M. Patel

• Paper: https://arxiv.org/abs/2411.17687
• Code: https://sudraj2002.github.io/gendegpage/

[Arxiv]Mixed Degradation Image Restoration via Local Dynamic Optimization and Conditional Embedding

Yubin Gu, Yuan Meng, Xiaoshuai Sun, Jiayi Ji, Weijian Ruan, Rongrong Ji

• Paper: https://arxiv.org/abs/2411.16217

[Arxiv]PromptHSI: Universal Hyperspectral Image Restoration Framework for Composite Degradation

Chia-Ming Lee, Ching-Heng Cheng, Yu-Fan Lin, Yi-Ching Cheng, Wo-Ting Liao, Chih-Chung Hsu, Fu-En Yang, Yu-Chiang Frank Wang

• Paper: https://arxiv.org/abs/2411.15922

[Arxiv]AllRestorer: All-in-One Transformer for Image Restoration under Composite Degradations

Jiawei Mao, Yu Yang, Xuesong Yin, Ling Shao, Hao Tang

• Paper: https://arxiv.org/abs/2411.10708

[Arxiv]All-in-one Weather-degraded Image Restoration via Adaptive Degradation-aware Self-prompting Model

Yuanbo Wen, Tao Gao, Ziqi Li, Jing Zhang, Kaihao Zhang, Ting Chen

• Paper: https://arxiv.org/abs/2411.07445

[Arxiv]Degradation-Aware Residual-Conditioned Optimal Transport for Unified Image Restoration

Xiaole Tang, Xiang Gu, Xiaoyi He, Xin Hu, Jian Sun

• Paper: https://arxiv.org/abs/2411.01656v1
• Code: https://github.com/xl-tang3/DA-RCOT

[Arxiv] An Intelligent Agentic System for Complex Image Restoration Problems

Kaiwen Zhu, Jinjin Gu, Zhiyuan You, Yu Qiao, Chao Dong

• Paper: https://arxiv.org/abs/2410.17809

[Arxiv] LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image Restoration

Yuang Ai, Huaibo Huang, Ran He

• Paper: https://arxiv.org/abs/2410.15385
• Code: https://github.com/shallowdream204/LoRA-IR

[ACCV2024]TANet: Triplet Attention Network for All-In-One Adverse Weather Image Restoration

Hsing-Hua Wang, Fu-Jen Tsai, Yen-Yu Lin, Chia-Wen Lin

• Paper: https://arxiv.org/abs/2410.08177
• Code: https://github.com/xhuachris/TANet-ACCV-2024

[ECCV2024]Restore Anything with Masks: Leveraging Mask Image Modeling for Blind All-in-One Image Restoration

Chu-Jie Qin, Rui-Qi Wu, Zikun Liu, Xin Lin, Chun-Le Guo, Hyun Hee Park, Chongyi Li

• Paper: https://arxiv.org/abs/2409.19403
• Code: https://github.com/Dragonisss/RAM

Accurate Forgetting for All-in-One Image Restoration Model

Xin Su, Zhuoran Zheng

• Paper: https://arxiv.org/abs/2409.00685

Perceive-IR: Learning to Perceive Degradation Better for All-in-One Image Restoration

Xu Zhang, Jiaqi Ma, Guoli Wang, Qian Zhang, Huan Zhang, Lefei Zhang

• Paper: https://arxiv.org/abs/2108.02774

[ACMMM2024]Learning A Low-Level Vision Generalist via Visual Task Prompt

Xiangyu Chen, Yihao Liu, Yuandong Pu, Wenlong Zhang, Jiantao Zhou, Yu Qiao, Chao Dong

• Paper: https://arxiv.org/abs/2408.08601
• Code: https://github.com/chxy95/GenLV

HAIR: Hypernetworks-based All-in-One Image Restoration

Jin Cao, Yi Cao, Li Pang, Deyu Meng, Xiangyong Cao

• Paper: https://arxiv.org/abs/2408.08091
• Code: https://github.com/toummHus/HAIR

Review Learning: Advancing All-in-One Ultra-High-Definition Image Restoration Training Method

Xin Su, Zhuoran Zheng, Chen Wu

• Paper: https://arxiv.org/abs/2408.06709

UniProcessor: A Text-induced Unified Low-level Image Processor

Huiyu Duan, Xiongkuo Min, Sijing Wu, Wei Shen, Guangtao Zhai

• Paper: https://arxiv.org/abs/2407.20928
• Code: https://github.com/IntMeGroup/UniProcessor

Multi-Expert Adaptive Selection: Task-Balancing for All-in-One Image Restoration

Xiaoyan Yu, Shen Zhou, Huafeng Li, Liehuang Zhu

• Paper: https://arxiv.org/abs/2407.19139

RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models

Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Sixiang Chen, Tian Ye, Renjing Pei, Kaiwen Zhou, Fenglong Song, Lei Zhu

• Paper: https://arxiv.org/abs/2407.18035

Training-Free Large Model Priors for Multiple-in-One Image Restoration

Xuanhua He, Lang Li, Yingying Wang, Hui Zheng, Ke Cao, Keyu Yan, Rui Li, Chengjun Xie, Jie Zhang, Man Zhou

• Paper: https://arxiv.org/abs/2407.13181

Any Image Restoration with Efficient Automatic Degradation Adaptation

Bin Ren, Eduard Zamfir, Yawei Li, Zongwei Wu, Danda Pani Paudel, Radu Timofte, Nicu Sebe, Luc Van Gool

• Paper: https://arxiv.org/abs/2407.13372
• Code: https://github.com/Amazingren/AnyIR

[ECCV2024]GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity

Shuo Cao, Yihao Liu, Wenlong Zhang, Yu Qiao, Chao Dong

• Paper: https://arxiv.org/abs/2407.12273

OneRestore: A Universal Restoration Framework for Composite Degradation

Yu Guo, Yuan Gao, Yuxu Lu, Huilin Zhu, Ryan Wen Liu, Shengfeng He

• Paper: https://arxiv.org/abs/2407.04621

Learning Frequency-Aware Dynamic Transformers for All-In-One Image Restoration

Zenglin Shi, Tong Su, Pei Liu, Yunpeng Wu, Le Zhang, Meng Wang

• Paper: https://arxiv.org/abs/2407.01636

Instruct-IPT: All-in-One Image Processing Transformer via Weight Modulation

Yuchuan Tian, Jianhong Han, Hanting Chen, Yuanyuan Xi, Guoyang Zhang, Jie Hu, Chao Xu, Yunhe Wang

• Paper: https://arxiv.org/abs/2407.00676
• Code: https://github.com/huawei-noah/Pretrained-IPT

ConStyle v2: A Strong Prompter for All-in-One Image Restoration

Dongqi Fan, Junhao Zhang, Liang Chang

• Paper: https://arxiv.org/abs/2406.18242
• Code: https://github.com/Dongqi-Fan/ConStyle_v2

Restorer: Removing Multi-Degradation with All-Axis Attention and Prompt Guidance

Jiawei Mao, Juncheng Wu, Yuyin Zhou, Xuesong Yin, Yuanqi Chang

• Paper: https://arxiv.org/abs/2406.12587
• Code: https://github.com/Talented-Q/Restorer

[MICCAI2024]All-In-One Medical Image Restoration via Task-Adaptive Routing

Zhiwen Yang, Haowei Chen, Ziniu Qian, Yang Yi, Hui Zhang, Dan Zhao, Bingzheng Wei, Yan Xu

• Paper: https://arxiv.org/abs/2405.19769
• Code: https://github.com/Yaziwel/All-In-One-Medical-Image-Restoration-via-Task-Adaptive-Routing.git

Efficient Degradation-aware Any Image Restoration

Eduard Zamfir, Zongwei Wu, Nancy Mehta, Danda Pani Paudel, Yulun Zhang, Radu Timofte

• Paper: https://arxiv.org/abs/2405.15475
• Code: https://eduardzamfir.github.io/daair/

[ACMMM24]Harmony in Diversity: Improving All-in-One Image Restoration via Multi-Task Collaboration

Gang Wu, Junjun Jiang, Kui Jiang, Xianming Liu

• Paper: https://openreview.net/pdf?id=aMgbnUqSHv
• Code: https://github.com/Aitical/Art

Referring Flexible Image Restoration

Runwei Guan, Rongsheng Hu, Zhuhao Zhou, Tianlang Xue, Ka Lok Man, Jeremy Smith, Eng Gee Lim, Weiping Ding, Yutao Yue

• Paper: https://arxiv.org/abs/2404.10342
• Code: https://github.com/GuanRunwei/FIR-CP

[CVPRW2024]Photo-Realistic Image Restoration in the Wild with Controlled Vision-Language Models

Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön

• Paper: https://arxiv.org/abs/2404.09732
• Code: https://github.com/Algolzw/daclip-uir

Joint Conditional Diffusion Model for Image Restoration with Mixed Degradations

Yufeng Yue, Meng Yu, Luojie Yang, Yi Yang

• Paper: https://arxiv.org/abs/2404.07770

Dynamic Pre-training: Towards Efficient and Scalable All-in-One Image Restoration

Akshay Dudhane, Omkar Thawakar, Syed Waqas Zamir, Salman Khan, Fahad Shahbaz Khan, Ming-Hsuan Yang

• Paper: https://arxiv.org/abs/2404.02154
• Code: https://github.com/akshaydudhane16/DyNet

WM-MoE: Weather-aware Multi-scale Mixture-of-Experts for Blind Adverse Weather Removal

Yulin Luo, Rui Zhao, Xiaobao Wei, Jinwei Chen, Yijie Lu, Shenghao Xie, Tianyu Wang, Ruiqin Xiong, Ming Lu, Shanghang Zhang

• Paper: https://arxiv.org/abs/2303.13739

AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation

Yuning Cui, Syed Waqas Zamir, Salman Khan, Alois Knoll, Mubarak Shah, Fahad Shahbaz Khan

• Paper: https://arxiv.org/abs/2403.14614
• Code: https://github.com/c-yn/AdaIR

[CVPR2024]Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model

Dian Zheng, Xiao-Ming Wu, Shuzhou Yang, Jian Zhang, Jian-Fang Hu, Wei-Shi Zheng

• Paper: https://arxiv.org/abs/2403.11157
• Code: https://github.com/iSEE-Laboratory/DiffUIR

Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network Structure

De Cheng, Yanling Ji, Dong Gong, Yan Li, Nannan Wang, Junwei Han, Dingwen Zhang

• Paper: https://arxiv.org/abs/2403.07292
• Code: https://github.com/xiaojihh/CL_all-in-one

AoSRNet: All-in-One Scene Recovery Networks via Multi-knowledge Integration

Yuxu Lu, Dong Yang, Yuan Gao, Ryan Wen Liu, Jun Liu, Yu Guo

• Paper: https://arxiv.org/abs/2402.03738
• Code: https://github.com/LouisYuxuLu/AoSRNet

[ECCV2024]InstructIR: High-Quality Image Restoration Following Human Instructions

Marcos V. Conde, Gregor Geigle, Radu Timofte

• Paper: https://arxiv.org/abs/2401.16468
• Code: https://github.com/mv-lab/InstructIR

Unified-Width Adaptive Dynamic Network for All-In-One Image Restoration

Yimin Xu, Nanxi Gao, Zhongyun Shan, Fei Chao, Rongrong Ji

• Paper: https://arxiv.org/abs/2401.13221
• Code: https://github.com/xuyimin0926/U-WADN

Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy

Xiangtao Kong, Chao Dong, Lei Zhang

• Paper: https://arxiv.org/abs/2401.03379
• Code: https://github.com/Xiangtaokong/MiOIR

2023

Improving Image Restoration through Removing Degradations in Textual Representations

Jingbo Lin, Zhilu Zhang, Yuxiang Wei, Dongwei Ren, Dongsheng Jiang, Wangmeng Zuo

• Paper: https://arxiv.org/pdf/2312.17334
• Code: https://github.com/mrluin/TextualDegRemoval

[AAAI2024]Efficient Deweather Mixture-of-Experts with Uncertainty-aware Feature-wise Linear Modulation

Rongyu Zhang, Yulin Luo, Jiaming Liu, Huanrui Yang, Zhen Dong, Denis Gudovskiy, Tomoyuki Okuno, Yohei Nakata, Kurt Keutzer, Yuan Du, Shanghang Zhang

• Paper: https://arxiv.org/abs/2312.16610

Textual Prompt Guided Image Restoration

Qiuhai Yan, Aiwen Jiang, Kang Chen, Long Peng, Qiaosi Yi, Chunjie Zhang

• Paper: https://arxiv.org/abs/2312.06162
• Code: https://github.com/MoTong-AI-studio/TextPromptIR

Decoupling Degradation and Content Processing for Adverse Weather Image Restoration

Xi Wang, Xueyang Fu, Peng-Tao Jiang, Jie Huang, Mi Zhou, Bo Li, Zheng-Jun Zha

• Paper: https://arxiv.org/abs/2312.05006

Prompt-In-Prompt Learning for Universal Image Restoration

Zilong Li, Yiming Lei, Chenglong Ma, Junping Zhang, Hongming Shan

• Paper: https://arxiv.org/abs/2312.05038v1
• Code: https://github.com/longzilicart/pip_universal

[CVPR2024]Multimodal Prompt Perceiver: Empower Adaptiveness, Generalizability and Fidelity for All-in-One Image Restoration

Yuang Ai, Huaibo Huang, Xiaoqiang Zhou, Jiexiang Wang, Ran He

• Paper: https://arxiv.org/abs/2312.02918

Language-driven All-in-one Adverse Weather Removal

Hao Yang, Liyuan Pan, Yan Yang, Wei Liang

• Paper: https://arxiv.org/abs/2312.01381

[ICML2024]Test-Time Degradation Adaptation for Open-Set Image Restoration

Yuanbiao Gou, Haiyu Zhao, Boyun Li, Xinyan Xiao, Xi Peng

• Paper: https://arxiv.org/abs/2312.02197
• Code: https://github.com/XLearning-SCU/2024-ICML-TAO

Clarity ChatGPT: An Interactive and Adaptive Processing System for Image Restoration and Enhancement

Yanyan Wei, Zhao Zhang, Jiahuan Ren, Xiaogang Xu, Richang Hong, Yi Yang, Shuicheng Yan, Meng Wang

• Paper: https://arxiv.org/abs/2311.11695

Always Clear Days: Degradation Type and Severity Aware All-In-One Adverse Weather Removal

Yu-Wei Chen, Soo-Chang Pei

• Paper: https://arxiv.org/abs/2310.18293
• Code: https://github.com/fordevoted/UtilityIR

Neural Degradation Representation Learning for All-In-One Image Restoration

Mingde Yao, Ruikang Xu, Yuanshen Guan, Jie Huang, Zhiwei Xiong

• Paper: https://arxiv.org/abs/2310.12848

AutoDIR: Automatic All-in-One Image Restoration with Latent Diffusion

Yitong Jiang, Zhaoyang Zhang, Tianfan Xue, Jinwei Gu

• Paper: https://arxiv.org/abs/2310.10123
• Code: https://jiangyitong.github.io/AutoDIR_webpage/

Unifying Image Processing as Visual Prompting Question Answering

Yihao Liu, Xiangyu Chen, Xianzheng Ma, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong

• Paper: https://arxiv.org/abs/2310.10513

[ICLR2024]Controlling Vision-Language Models for Universal Image Restoration

• Paper: https://arxiv.org/abs/2310.01018
• Code: https://github.com/Algolzw/daclip-uir

[STACOM2023]Fill the K-Space and Refine the Image: Prompting for Dynamic and Multi-Contrast MRI Reconstruction

Bingyu Xin, Meng Ye, Leon Axel, Dimitris N. Metaxas

• Paper: https://arxiv.org/pdf/2309.13839
• Code: https://github.com/hellopipu/PromptMR

[TCSVT2024]Prompt-based Ingredient-Oriented All-in-One Image Restoration

Hu Gao, Depeng Dang

• Paper: https://arxiv.org/abs/2309.03063

[ACMMM2023]All-in-one Multi-degradation Image Restoration Network via Hierarchical Degradation Representation

Cheng Zhang, Yu Zhu, Qingsen Yan, Jinqiu Sun, Yanning Zhang

• Paper: https://arxiv.org/abs/2308.03021

Decomposition Ascribed Synergistic Learning for Unified Image Restoration

Jinghao Zhang, Feng Zhao

• Paper: https://arxiv.org/abs/2308.00759

DRM-IR: Task-Adaptive Deep Unfolding Network for All-In-One Image Restoration

Yuanshuo Cheng, Mingwen Shao, Yecong Wan, Chao Wang

• Paper: https://arxiv.org/abs/2307.07688

ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration

Jiaqi Ma, Tianheng Cheng, Guoli Wang, Qian Zhang, Xinggang Wang, Lefei Zhang

• Paper: https://arxiv.org/abs/2306.13653

[NeurIPS2023]PromptIR: Prompting for All-in-One Blind Image Restoration

Vaishnav Potlapalli, Syed Waqas Zamir, Salman Khan, Fahad Shahbaz Khan

• Paper: https://arxiv.org/abs/2306.13090
• Code: https://github.com/va1shn9v/PromptIR

[IJCV2023]GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditions

Tao Wang, Kaihao Zhang, Ziqian Shao, Wenhan Luo, Bjorn Stenger, Tong Lu, Tae-Kyun Kim, Wei Liu, Hongdong Li

• Paper: https://arxiv.org/abs/2305.17863v2
• Code: https://github.com/TaoWangzj/GridFormer

[CVPR2023]Generative Diffusion Prior for Unified Image Restoration and Enhancement

Ben Fei, Zhaoyang Lyu, Liang Pan, Junzhe Zhang, Weidong Yang, Tianyue Luo, Bo Zhang, Bo Dai

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

[CVPR2023]Context-aware Pretraining for Efficient Blind Image Decomposition

Chao Wang, Zhedong Zheng, Ruijie Quan, Yifan Sun, Yi Yang

• Paper: https://openaccess.thecvf.com/content/CVPR2023/papers/Wang_Context-Aware_Pretraining_for_Efficient_Blind_Image_Decomposition_CVPR_2023_paper.pdf

[CVPR2023]Ingredient-oriented Multi-Degradation Learning for Image Restoration

Jinghao Zhang, Jie Huang, Mingde Yao, Zizheng Yang, Hu Yu, Man Zhou, Feng Zhao

• Paper: https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_Ingredient-Oriented_Multi-Degradation_Learning_for_Image_Restoration_CVPR_2023_paper.pdf

[CVPR2023]Learning Weather-General and Weather-Specific Features for Image Restoration Under Multiple Adverse Weather Conditions

Yurui Zhu, Tianyu Wang, Xueyang Fu, Xuanyu Yang, Xin Guo, Jifeng Dai, Yu Qiao, Xiaowei Hu

• Paper: https://openaccess.thecvf.com/content/CVPR2023/papers/Zhu_Learning_Weather-General_and_Weather-Specific_Features_for_Image_Restoration_Under_Multiple_CVPR_2023_paper.pdf
• Code: https://github.com/zhuyr97/WGWS-Net

[ICCV2023]Adverse Weather Removal with Codebook Priors

Tian Ye1, Sixiang Chen, Jinbin Bai, Jun Shi, Chenghao Xue,Jingxia Jiang, Junjie Yin, Erkang Chen, Yun Liu

• Paper: https://openaccess.thecvf.com/content/ICCV2023/papers/Ye_Adverse_Weather_Removal_with_Codebook_Priors_ICCV_2023_paper.pdf

[TPAMI2023]Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models

Ozan Özdenizci, Robert Legenstein

• Paper: https://arxiv.org/abs/2207.14626

[CVPR2023]Images Speak in Images: A Generalist Painter for In-Context Visual Learning

Xinlong Wang, Wen Wang, Yue Cao, Chunhua Shen, Tiejun Huang

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

2022

[CVPR2022]All-In-One Image Restoration for Unknown Corruption

Boyun Li, Xiao Liu, Peng Hu, Zhongqin Wu, Jiancheng Lv, Xi Peng

• 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.git

[CVPR2022]TAPE: Task-Agnostic Prior Embedding for Image Restoration

Lin Liu, Lingxi Xie, Xiaopeng Zhang, Shanxin Yuan, Xiangyu Chen, Wengang Zhou, Houqiang Li, Qi Tian

• Paper: https://arxiv.org/abs/2203.06074

[CVPR2022]Learning Multiple Adverse Weather Removal via Two-stage Knowledge Learning and Multi-contrastive Regularization: Toward a Unified Model

Wei-Ting Chen, Zhi-Kai Huang, Cheng-Che Tsai, Hao-Hsiang Yang, Jian-Jiun Ding, Sy-Yen Kuo

• 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

2021

On Efficient Transformer-Based Image Pre-training for Low-Level Vision

Wenbo Li, Xin Lu, Shengju Qian, Jiangbo Lu, Xiangyu Zhang, Jiaya Jia

• Paper: https://arxiv.org/abs/2112.10175
• Code: https://github.com/fenglinglwb/EDT

[CVPR2022]TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions

Jeya Maria Jose Valanarasu, Rajeev Yasarla, Vishal M. Patel

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

[ECCV2022]Blind Image Decomposition

Junlin Han, Weihao Li, Pengfei Fang, Chunyi Sun, Jie Hong, Mohammad Ali Armin, Lars Petersson, Hongdong Li

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

2020

[CVPR2021] Pre-Trained Image Processing Transformer

Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu, Wen Gao

• Paper: https://arxiv.org/abs/2012.00364
• Code: https://github.com/huawei-noah/Pretrained-IPT

[CVPR2020] All in One Bad Weather Removal Using Architectural Search

Ruoteng Li, Robby T. Tan, Loong-Fah Cheong

• Paper: https://openaccess.thecvf.com/content_CVPR_2020/papers/Li_All_in_One_Bad_Weather_Removal_Using_Architectural_Search_CVPR_2020_paper.pdf

2019

[TPAMI2019] A General Decoupled Learning Framework for Parameterized Image Operators

Qingnan Fan, Dongdong Chen, Lu Yuan, Gang Hua, Nenghai Yu, Baoquan Chen

• Paper: https://arxiv.org/abs/1907.05852