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Motion blur is a common photography artifact in dynamic environments that typically comes jointly with the other types of degradation.
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Adaptive deblocking filter
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Blocking artifacts suppression in block-coded images using overcomplete wavelet representation
AW-C Liew and Hong Yan · 2004
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, Eero P Simoncelli, et al · 2004
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Fast motion deblurring
Sunghyun Cho and Seungyong Lee · 2009
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ImageNet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Understanding and evaluating blind deconvolution algorithms
Anat Levin, Yair Weiss, Fredo Durand, and William T Freeman · 2009
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Two-phase kernel estimation for robust motion deblurring
Li Xu and Jiaya Jia · 2010
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Reducing artifacts in jpeg decompression via a learned dictionary
Huibin Chang, Michael K Ng, and Tieyong Zeng · 2013
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Dynamic scene deblurring
Tae Hyun Kim, Byeongjoo Ahn, and Kyoung Mu Lee · 2013
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Rectifier nonlinearities improve neural network acoustic models
Andrew L Maas, Awni Y Hannun, and Andrew Y Ng · 2013
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Learning a deep convolutional network for image super-resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
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Segmentation-free dynamic scene deblurring
Tae Hyun Kim and Kyoung Mu Lee · 2014
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A contrast enhancement framework with jpeg artifacts suppression
Yu Li, Fangfang Guo, Robby T Tan, and Michael S Brown · 2014
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Post-processing for blocking artifact reduction based on inter-block correlation
Seok Bong Yoo, Kyuha Choi, and Jong Beom Ra · 2014
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Compression artifacts reduction by a deep convolutional network
Chao Dong, Yubin Deng, Chen Change Loy, and Xiaoou Tang · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Data-driven sparsity-based restoration of jpeg-compressed images in dual transform-pixel domain
Xianming Liu, Xiaolin Wu, Jiantao Zhou, and Debin Zhao · 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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Multi-scale context aggregation by dilated convolutions
Fisher Yu and Vladlen Koltun · 2015
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Accelerating the super-resolution convolutional neural network
Chao Dong, Chen Change Loy, and Xiaoou Tang · 2016
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Building dual-domain representations for compression artifacts reduction
Jun Guo and Hongyang Chao · 2016
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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Accurate image super-resolution using very deep convolutional networks
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
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Random walk graph laplacian-based smoothness prior for soft decoding of jpeg images
Xianming Liu, Gene Cheung, Xiaolin Wu, and Debin Zhao · 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 Huszar, Johannes Totz, Andrew P. Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang · 2016
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Compression artifacts removal using convolutional neural networks
Pavel Svoboda, Michal Hradis, David Barina, and Pavel Zemcik · 2016
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Seven ways to improve example-based single image super resolution
Radu Timofte, Rasmus Rothe, and Luc Van Gool · 2016
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Instance normalization: The missing ingredient for fast stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2016
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NTIRE 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
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One-to-many network for visually pleasing compression artifacts reduction
Jun Guo and Hongyang Chao · 2017
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Deep laplacian pyramid networks for fast and accurate super-resolution
Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, and Ming-Hsuan Yang · 2017
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Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, and Wenzhe Shi · 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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Deep multi-scale convolutional neural network for dynamic scene deblurring
Seungjun Nah, Tae Hyun Kim, and Kyoung Mu Lee · 2017
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Motion deblurring in the wild
Mehdi Noroozi, Paramanand Chandramouli, and Paolo Favaro · 2017
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Deep video deblurring for hand-held cameras
Shuochen Su, Mauricio Delbracio, Jue Wang, Guillermo Sapiro, Wolfgang Heidrich, and Oliver Wang · 2017
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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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Image super-resolution using dense skip connections
Tong Tong, Gen Li, Xiejie Liu, and Qinquan Gao · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Learning to super-resolve blurry face and text images
Xiangyu Xu, Deqing Sun, Jinshan Pan, Yujin Zhang, Hanspeter Pfister, and Ming-Hsuan Yang · 2017
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Deep back-projection networks for super-resolution
Muhammad Haris, Gregory Shakhnarovich, and Norimichi Ukita · 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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Multi-level wavelet-cnn for image restoration
Deformable ConvNets V2: More deformable, better results
Xizhou Zhu, Han Hu, Stephen Lin, and Jifeng Dai · 2019
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Densely residual laplacian super-resolution
Saeed Anwar and Nick Barnes · 2020
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High-resolution dual-stage multi-level feature aggregation for single image and video deblurring
Stephan Brehm, Sebastian Scherer, and Rainer Lienhart · 2020
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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 · 2020
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Closed-loop matters: Dual regression networks for single image super-resolution
Yong Guo, Jian Chen, Jingdong Wang, Qi Chen, Jiezhang Cao, Zeshuai Deng, Yanwu Xu, and Mingkui Tan · 2020
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Pengju Liu, Hongzhi Zhang, Kai Zhang, Liang Lin, and Wangmeng Zuo · 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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ESRGAN: Enhanced super-resolution generative adversarial networks
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy · 2018
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Image restoration by estimating frequency distribution of local patches
Jaeyoung Yoo, Sang-ho Lee, and Nojun Kwak · 2018
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Wide activation for efficient and accurate image super-resolution
Jiahui Yu, Yuchen Fan, Jianchao Yang, Ning Xu, Zhaowen Wang, Xinchao Wang, and Thomas Huang · 2018
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Crafting a toolchain for image restoration by deep reinforcement learning
Ke Yu, Chao Dong, Liang Lin, and Chen Change Loy · 2018
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MDCN: Multi-scale dense cross network for image super-resolution
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Residual feature distillation network for lightweight image super-resolution
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Improving convolutional networks with self-calibrated convolutions
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MMDM: Multi-frame and multi-scale for image demoireing
Shuai Liu, Chenghua Li, Nan Nan, Ziyao Zong, and Ruixia Song · 2020
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Image super-resolution with cross-scale non-local attention and exhaustive self-exemplars mining
Yiqun Mei, Yuchen Fan, Yuqian Zhou, Lichao Huang, Thomas S. Huang, and Honghui Shi · 2020
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NTIRE 2020 challenge on image and video deblurring
Seungjun Nah, Sanghyun Son, Radu Timofte, and Kyoung Mu Lee · 2020
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Multi-temporal recurrent neural networks for progressive non-uniform single image deblurring with incremental temporal training
Dongwon Park, Dong Un Kang, Jisoo Kim, and Se Young Chun · 2020
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Real-world blur dataset for learning and benchmarking deblurring algorithms
Jaesung Rim, Haeyun Lee, Jucheol Won, and Sunghyun Cho · 2020
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Spatially-attentive patch-hierarchical network for adaptive motion deblurring
Maitreya Suin, Kuldeep Purohit, and A. N. Rajagopalan · 2020
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Dual super-resolution learning for semantic segmentation
Li Wang, Dong Li, Yousong Zhu, Lu Tian, and Yi Shan · 2020
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Moire pattern removal via attentive fractal network
Dejia Xu, Yihao Chu, and Qingyan Sun · 2020
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Efficient dynamic scene deblurring using spatially variant deconvolution network with optical flow guided training
Yuan Yuan, Wei Su, and Dandan Ma · 2020
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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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Efficient image super-resolution using pixel attention
Hengyuan Zhao, Xiangtao Kong, Jingwen He, Yu Qiao, and Chao Dong · 2020
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Efficient spatio-temporal recurrent neural network for video deblurring
Zhihang Zhong, Ye Gao, Yinqiang Zheng, and Bo Zheng · 2020
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NTIRE 2021 challenge for defocus deblurring using dual-pixel images: Methods and results
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