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Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoration and related tasks.
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
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Image denoising by sparse 3-D transform-domain collaborative filtering
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
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Deep photo: Model-based photograph enhancement and viewing
Johannes Kopf, Boris Neubert, Billy Chen, Michael Cohen, Daniel Cohen-Or, Oliver Deussen, Matt Uyttendaele, and Dani Lischinski · 2008
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Single image haze removal using dark channel prior
Kaiming He, Jian Sun, and Xiaoou Tang · 2010
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Color demosaicking by local directional interpolation and nonlocal adaptive thresholding
Lei Zhang, Xiaolin Wu, Antoni Buades, and Xin Li · 2011
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Nonparametric blind super-resolution
Tomer Michaeli and Michal Irani · 2013
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Anchored neighborhood regression for fast example-based super-resolution
Radu Timofte, Vincent De Smet, and Luc Van Gool · 2013
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Unnatural l0 sparse representation for natural image deblurring
Li Xu, Shicheng Zheng, and Jiaya Jia · 2013
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Single image super-resolution from transformed self-exemplars
Jia-Bin Huang, Abhishek Singh, and Narendra Ahuja · 2015
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U-Net: convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Just noticeable defocus blur detection and estimation
Jianping Shi, Li Xu, and Jiaya Jia · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Gaussian error linear units (GELUs)
Dan Hendrycks and Kevin Gimpel · 2016
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Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang · 2016
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Language modeling with gated convolutional networks
Yann N Dauphin, Angela Fan, Michael Auli, and David Grangier · 2017
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Clearing the skies: A deep network architecture for single-image rain removal
Xueyang Fu, Jiabin Huang, Xinghao Ding, Yinghao Liao, and John Paisley · 2017
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Removing rain from single images via a deep detail network
Xueyang Fu, Jiabin Huang, Delu Zeng, Yue Huang, Xinghao Ding, and John Paisley · 2017
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Edge-based defocus blur estimation with adaptive scale selection
Ali Karaali and Claudio Rosito Jung · 2017
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Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
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SGDR: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2017
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Deep multi-scale convolutional neural network for dynamic scene deblurring
Seungjun Nah, Tae Hyun Kim, and Kyoung Mu Lee · 2017
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Benchmarking denoising algorithms with real photographs
Tobias Plotz and Stefan Roth · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 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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Learning deep cnn denoiser prior for image restoration
Kai Zhang, Wangmeng Zuo, Shuhang Gu, and Lei Zhang · 2017
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A high-quality denoising dataset for smartphone cameras
Abdelrahman Abdelhamed, Stephen Lin, and Michael S Brown · 2018
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DeblurGAN: Blind motion deblurring using conditional adversarial networks
Orest Kupyn, Volodymyr Budzan, Mykola Mykhailych, Dmytro Mishkin, and Jiří Matas · 2018
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Recurrent squeeze-and-excitation context aggregation net for single image deraining
Xia Li, Jianlong Wu, Zhouchen Lin, Hong Liu, and Hongbin Zha · 2018
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Non-local recurrent network for image restoration
Ding Liu, Bihan Wen, Yuchen Fan, Chen Change Loy, and Thomas S Huang · 2018
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Multi-level wavelet-cnn for image restoration
Pengju Liu, Hongzhi Zhang, Kai Zhang, Liang Lin, and Wangmeng Zuo · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Scale-recurrent network for deep image deblurring
Xin Tao, Hongyun Gao, Xiaoyong Shen, Jue Wang, and Jiaya Jia · 2018
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Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
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Density-aware single image de-raining using a multi-stream dense network
He Zhang and Vishal M Patel · 2018
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Dynamic scene deblurring using spatially variant recurrent neural networks
Jiawei Zhang, Jinshan Pan, Jimmy Ren, Yibing Song, Linchao Bao, Rynson WH Lau, and Ming-Hsuan Yang · 2018
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FFDNet: Toward a fast and flexible solution for CNN-based image denoising
Kai Zhang, Wangmeng Zuo, and Lei Zhang · 2018
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Image super-resolution using very deep residual channel attention networks
Yulun Zhang, Kunpeng Li, Kai Li, Lichen Wang, Bineng Zhong, and Yun Fu · 2018
Cited alongside, same era.
NTIRE 2019 challenge on real image denoising: Methods and results
Abdelrahman Abdelhamed, Radu Timofte, and Michael S Brown · 2019
Cited alongside, same era.
Real image denoising with feature attention
Saeed Anwar and Nick Barnes · 2019
Cited alongside, same era.
A deep journey into super-resolution: A survey
Saeed Anwar, Salman Khan, and Nick Barnes · 2019
Cited alongside, same era.
Dynamic scene deblurring with parameter selective sharing and nested skip connections
Hongyun Gao, Xin Tao, Xiaoyong Shen, and Jiaya Jia · 2019
Cited alongside, same era.
Self-guided network for fast image denoising
Shuhang Gu, Yawei Li, Luc Van Gool, and Radu Timofte · 2019
Cited alongside, same era.
Deep learning on image denoising: An overview
Chunwei Tian, Lunke Fei, Wenxian Zheng, Yong Xu, Wangmeng Zuo, and Chia-Wen Lin · 2020
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Image denoising using deep cnn with batch renormalization
Chunwei Tian, Yong Xu, and Wangmeng Zuo · 2020
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Identifying recurring patterns with deep neural networks for natural image denoising
Zhihao Xia and Ayan Chakrabarti · 2020
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Learning texture transformer network for image super-resolution
Fuzhi Yang, Huan Yang, Jianlong Fu, Hongtao Lu, and Baining Guo · 2020
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Dual adversarial network: Toward real-world noise removal and noise generation
Zongsheng Yue, Qian Zhao, Lei Zhang, and Deyu Meng · 2020
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CycleISP: Real image restoration via improved data synthesis
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, and Ling Shao · 2020
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Toward convolutional blind denoising of real photographs
Shi Guo, Zifei Yan, Kai Zhang, Wangmeng Zuo, and Lei Zhang · 2019
Cited alongside, same era.
Elad Hoffer, Berry Weinstein, Itay Hubara, Tal Ben-Nun, Torsten Hoefler, and Daniel Soudry · 2019
Cited alongside, same era.
NTIRE 2019 challenge on image enhancement: Methods and results
Andrey Ignatov and Radu Timofte · 2019
Cited alongside, same era.
Focnet: A fractional optimal control network for image denoising
Xixi Jia, Sanyang Liu, Xiangchu Feng, and Lei Zhang · 2019
Cited alongside, same era.
DeblurGAN-v2: Deblurring (orders-of-magnitude) faster and better
Orest Kupyn, Tetiana Martyniuk, Junru Wu, and Zhangyang Wang · 2019
Cited alongside, same era.
Deep defocus map estimation using domain adaptation
Junyong Lee, Sungkil Lee, Sunghyun Cho, and Seungyong Lee · 2019
Cited alongside, same era.
Later among the works it cites.
Learning enriched features for real image restoration and enhancement
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, and Ling Shao · 2020
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Deblurring by realistic blurring
Kaihao Zhang, Wenhan Luo, Yiran Zhong, Lin Ma, Bjorn Stenger, Wei Liu, and Hongdong Li · 2020
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Residual dense network for image restoration
Yulun Zhang, Yapeng Tian, Yu Kong, Bineng Zhong, and Yun Fu · 2020
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Deformable DETR: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
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Learning to reduce defocus blur by realistically modeling dual-pixel data
Abdullah Abuolaim, Mauricio Delbracio, Damien Kelly, Michael S. Brown, and Peyman Milanfar · 2021
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NTIRE 2021 challenge for defocus deblurring using dual-pixel images: Methods and results
Abdullah Abuolaim, Radu Timofte, and Michael S Brown · 2021
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Pre-trained image processing transformer
Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu, and Wen Gao · 2021
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Rethinking coarse-to-fine approach in single image deblurring
Sung-Jin Cho, Seo-Won Ji, Jun-Pyo Hong, Seung-Won Jung, and Sung-Jea Ko · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2021
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Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity
William Fedus, Barret Zoph, and Noam Shazeer · 2021
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Kodak lossless true color image suite
Rich Franzen · 2021
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Transformers in vision: A survey
Salman Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, and Mubarak Shah · 2021
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Colorization transformer
Manoj Kumar, Dirk Weissenborn, and Nal Kalchbrenner · 2021
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Iterative filter adaptive network for single image defocus deblurring
Junyong Lee, Hyeongseok Son, Jaesung Rim, Sunghyun Cho, and Seungyong Lee · 2021
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SwinIR: Image restoration using swin transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Dynamic attentive graph learning for image restoration
Chong Mou, Jian Zhang, and Zhuoyuan Wu · 2021
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Ntire 2021 challenge on image deblurring
Seungjun Nah, Sanghyun Son, Suyoung Lee, Radu Timofte, and Kyoung Mu Lee · 2021
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Spatially-adaptive image restoration using distortion-guided networks
Kuldeep Purohit, Maitreya Suin, AN Rajagopalan, and Vishnu Naresh Boddeti · 2021
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Adaptive consistency prior based deep network for image denoising
Chao Ren, Xiaohai He, Chuncheng Wang, and Zhibo Zhao · 2021
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Single image defocus deblurring using kernel-sharing parallel atrous convolutions
Hyeongseok Son, Junyong Lee, Sunghyun Cho, and Seungyong Lee · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
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Uformer: A general u-shaped transformer for image restoration
Zhendong Wang, Xiaodong Cun, Jianmin Bao, and Jianzhuang Liu · 2021
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Segformer: Simple and efficient design for semantic segmentation with transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M Alvarez, and Ping Luo · 2021
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Tokens-to-token vit: Training vision transformers from scratch on imagenet
Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Zihang Jiang, Francis EH Tay, Jiashi Feng, and Shuicheng Yan · 2021
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Multi-stage progressive image restoration
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, and Ling Shao · 2021
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Plug-and-play image restoration with deep denoiser prior
Kai Zhang, Yawei Li, Wangmeng Zuo, Lei Zhang, Luc Van Gool, and Radu Timofte · 2021
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Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip HS Torr, et al · 2021
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Burst image restoration and enhancement
Akshay Dudhane, Syed Waqas Zamir, Salman Khan, Fahad Khan, and Ming-Hsuan Yang · 2022
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