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Existing Image Restoration (IR) studies typically focus on task-specific or universal modes individually, relying on the mode selection of users and lacking the cooperation between multiple task-specific/universal restoration modes.
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
David Martin, Charless Fowlkes, Doron Tal, and Jitendra Malik · 2001
Earlier work this paper cites.
Color demosaicking by local directional interpolation and nonlocal adaptive thresholding
Lei Zhang, Xiaolin Wu, Antoni Buades, and Xin Li · 2011
Earlier work this paper cites.
Single image super-resolution from transformed self-exemplars
Jia-Bin Huang, Abhishek Singh, and Narendra Ahuja · 2015
Earlier work this paper cites.
Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
Earlier work this paper cites.
Blind image deblurring using dark channel prior
Jinshan Pan, Deqing Sun, Hanspeter Pfister, and Ming-Hsuan Yang · 2016
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Artificial intelligence: a modern approach
Stuart J Russell and Peter Norvig · 2016
Earlier work this paper cites.
Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
Earlier work this paper cites.
Deep generative adversarial compression artifact removal
Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, and Alberto Del Bimbo · 2017
Earlier work this paper cites.
Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al · 2017
Earlier work this paper cites.
Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
Earlier work this paper cites.
Ntire 2017 challenge on single image super-resolution: Methods and results
Radu Timofte, Eirikur Agustsson, Luc Van Gool, Ming-Hsuan Yang, and Lei Zhang · 2017
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Attention is all you need
A Vaswani · 2017
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Learning blind motion deblurring
Patrick Wieschollek, Michael Hirsch, Bernhard Scholkopf, and Hendrik Lensch · 2017
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Deep joint rain detection and removal from a single image
Wenhan Yang, Robby T Tan, Jiashi Feng, Jiaying Liu, Zongming Guo, and Shuicheng Yan · 2017
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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2017
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Cycle-dehaze: Enhanced cyclegan for single image dehazing
Deniz Engin, Anil Genç, and Hazim Kemal Ekenel · 2018
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Attentive generative adversarial network for raindrop removal from a single image
Rui Qian, Robby T Tan, Wenhan Yang, Jiajun Su, and Jiaying Liu · 2018
Earlier work this paper cites.
Scale-recurrent network for deep image deblurring
Xin Tao, Hongyun Gao, Xiaoyong Shen, Jue Wang, and Jiaya Jia · 2018
Earlier work this paper cites.
Gladnet: Low-light enhancement network with global awareness
Wenjing Wang, Chen Wei, Wenhan Yang, and Jiaying Liu · 2018
Earlier work this paper cites.
Deep retinex decomposition for low-light enhancement. arxiv 2018
C Wei, W Wang, W Yang, and J Liu · 2018
Earlier work this paper cites.
Crafting a toolchain for image restoration by deep reinforcement learning
Ke Yu, Chao Dong, Liang Lin, and Chen Change Loy · 2018
Earlier work this paper cites.
Brief review of image denoising techniques
Linwei Fan, Fan Zhang, Hui Fan, and Caiming Zhang · 2019
Earlier work this paper cites.
Densely connected hierarchical network for image denoising
Bumjun Park, Songhyun Yu, and Jechang Jeong · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Fast underwater image enhancement for improved visual perception
Md Jahidul Islam, Youya Xia, and Junaed Sattar · 2020
Cited alongside, same era.
Learning disentangled feature representation for hybrid-distorted image restoration
Xin Li, Xin Jin, Jianxin Lin, Sen Liu, Yaojun Wu, Tao Yu, Wei Zhou, and Zhibo Chen · 2020
Cited alongside, same era.
Ffa-net: Feature fusion attention network for single image dehazing
Xu Qin, Zhilin Wang, Yuanchao Bai, Xiaodong Xie, and Huizhu Jia · 2020
Cited alongside, same era.
Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Gpt-4 technical report, 2023
OpenAI · 2023
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Restoring vision in adverse weather conditions with patch-based denoising diffusion models
Ozan Özdenizci and Robert Legenstein · 2023
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Promptir: Prompting for all-in-one blind image restoration
Vaishnav Potlapalli, Syed Waqas Zamir, Salman Khan, and Fahad Shahbaz Khan · 2023
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Code llama: Open foundation models for code
Baptiste Roziere, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, et al · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, and Yuxiong He · 2020
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Cited alongside, same era.
Early exit or not: Resource-efficient blind quality enhancement for compressed images
Qunliang Xing, Mai Xu, Tianyi Li, and Zhenyu Guan · 2020
Cited alongside, same era.
Kodak lossless true color image suite
Rich Franzen · 2021
Cited alongside, same era.
Learning dual priors for jpeg compression artifacts removal
Xueyang Fu, Xi Wang, Aiping Liu, Junwei Han, and Zheng-Jun Zha · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
Cited alongside, same era.
Towards flexible blind jpeg artifacts removal
Jiaxi Jiang, Kai Zhang, and Radu Timofte · 2021
Cited alongside, same era.
Later among the works it cites.
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, and Meng Wang · 2023
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Diffir: Efficient diffusion model for image restoration
Bin Xia, Yulun Zhang, Shiyin Wang, Yitong Wang, Xinglong Wu, Yapeng Tian, Wenming Yang, and Luc Van Gool · 2023
Later among the works it cites.
Octopus: Embodied vision-language programmer from environmental feedback
Jingkang Yang, Yuhao Dong, Shuai Liu, Bo Li, Ziyue Wang, Chencheng Jiang, Haoran Tan, Jiamu Kang, Yuanhan Zhang, Kaiyang Zhou, et al · 2023
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mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration
Qinghao Ye, Haiyang Xu, Jiabo Ye, Ming Yan, Haowei Liu, Qi Qian, Ji Zhang, Fei Huang, and Jingren Zhou · 2023
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Jin Cao, Deyu Meng, and Xiangyong Cao · 2024
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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, and Lei Zhu · 2024
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High-quality image restoration following human instructions
Marcos V Conde, Gregor Geigle, and Radu Timofte · 2024
Later among the works it cites.
Onerestore: A universal restoration framework for composite degradation
Yu Guo, Yuan Gao, Yuxu Lu, Huilin Zhu, Ryan Wen Liu, and Shengfeng He · 2024
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2024
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Embodiedgpt: Vision-language pre-training via embodied chain of thought
Yao Mu, Qinglong Zhang, Mengkang Hu, Wenhai Wang, Mingyu Ding, Jun Jin, Bin Wang, Jifeng Dai, Yu Qiao, and Ping Luo · 2024
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Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom · 2024
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Scaling llm test-time compute optimally can be more effective than scaling model parameters
Charlie Snell, Jaehoon Lee, Kelvin Xu, and Aviral Kumar · 2024
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Coser: Bridging image and language for cognitive super-resolution
Haoze Sun, Wenbo Li, Jianzhuang Liu, Haoyu Chen, Renjing Pei, Xueyi Zou, Youliang Yan, and Yujiu Yang · 2024
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Towards open-ended visual quality comparison, 2024
Haoning Wu, Hanwei Zhu, Zicheng Zhang, Erli Zhang, Chaofeng Chen, Liang Liao, Chunyi Li, Annan Wang, Wenxiu Sun, Qiong Yan, Xiaohong Liu, Guangtao Zhai, Shiqi Wang, and Weisi Lin · 2024
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Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild
Fanghua Yu, Jinjin Gu, Zheyuan Li, Jinfan Hu, Xiangtao Kong, Xintao Wang, Jingwen He, Yu Qiao, and Chao Dong · 2024
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An intelligent agentic system for complex image restoration problems
Kaiwen Zhu, Jinjin Gu, Zhiyuan You, Yu Qiao, and Chao Dong · 2024
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Uniprocessor: a text-induced unified low-level image processor
Huiyu Duan, Xiongkuo Min, Sijing Wu, Wei Shen, and Guangtao Zhai · 2025
Closest in time.
Moe-diffir: Task-customized diffusion priors for universal compressed image restoration
Yulin Ren, Xin Li, Bingchen Li, Xingrui Wang, Mengxi Guo, Shijie Zhao, Li Zhang, and Zhibo Chen · 2025
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