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Single image super-resolution (SISR) deals with a fundamental problem of upsampling a low-resolution (LR) image to its high-resolution (HR) version.
Scale-space and edge detection using anisotropic diffusion
Pietro Perona and Jitendra Malik · 1990
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Total variation based image restoration with free local constraints
Leonid I Rudin and Stanley Osher · 1994
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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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Human facial illustrations: Creation and psychophysical evaluation
Bruce Gooch, Erik Reinhard, and Amy Gooch · 2004
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Real-time video abstraction
Holger Winnemöller, Sven C Olsen, and Bruce Gooch · 2006
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Coherent line drawing
Henry Kang, Seungyong Lee, and Charles K Chui · 2007
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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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Image abstraction by structure adaptive filtering
Jan Eric Kyprianidis and Jürgen Döllner · 2008
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Image super-resolution via sparse representation
Jiao Yang, John Wright, Thomas S Huang, and Yi Ma · 2010
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On single image scale-up using sparse-representations
Roman Zeyde, Michael Elad, and Matan Protter · 2010
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An introduction to total variation for image analysis
Antonin Chambolle, Vicent Caselles, Daniel Cremers, Matteo Novaga, and Thomas Pock · 2010
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Dictionary learning for deblurring and digital zoom
Florent Couzinie-Devy, Julien Mairal, Francis Bach, and Jean Ponce · 2011
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From learning models of natural image patches to whole image restoration
Daniel Zoran and Yair Weiss · 2011
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Coupled dictionary training for image super-resolution
Jianchao Yang, Zhaowen Wang, Zhe Lin, Scott Cohen, and Thomas Huang · 2012
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Low-complexity single-image super-resolution based on nonnegative neighbor embedding
Marco Bevilacqua, Aline Roumy, Christine Guillemot, and Marie Line Alberi-Morel · 2012
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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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Learning a deep convolutional network for image super-resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
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Smpl: A skinned multi-person linear model
Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J Black · 2015
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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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Raisr: Rapid and accurate image super resolution
Yaniv Romano, John Isidoro, and Peyman Milanfar · 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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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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Deeply-recursive convolutional network for image super-resolution
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
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Visual dynamics: Probabilistic future frame synthesis via cross convolutional networks
Tianfan Xue, Jiajun Wu, Katherine Bouman, and Bill Freeman · 2016
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Dynamic filter networks
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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Deep back-projection networks for super-resolution
Muhammad Haris, Gregory Shakhnarovich, and Norimichi Ukita · 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
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Learning a single convolutional super-resolution network for multiple degradations
Kai Zhang, Wangmeng Zuo, and Lei Zhang · 2018
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Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation
Younghyun Jo, Seoung Wug Oh, Jaeyeon Kang, and Seon Joo Kim · 2018
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Burst denoising with kernel prediction networks
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Xu Jia, Bert De Brabandere, Tinne Tuytelaars, and Luc V Gool · 2016
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Weight normalization: A simple reparameterization to accelerate training of deep neural networks
Tim Salimans and Durk P Kingma · 2016
Cited alongside, same era.
Towards deep compositional networks
Domen Tabernik, Matej Kristan, Jeremy L Wyatt, and Aleš Leonardis · 2016
Cited alongside, same era.
Accelerating the super-resolution convolutional neural network
Chao Dong, Chen Change Loy, and Xiaoou Tang · 2016
Cited alongside, same era.
Deep laplacian pyramid networks for fast and accurate super-resolution
Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, and Ming-Hsuan Yang · 2017
Cited alongside, same era.
Image super-resolution via deep recursive residual network
Ying Tai, Jian Yang, and Xiaoming Liu · 2017
Cited alongside, same era.
Kernel-predicting convolutional networks for denoising monte carlo renderings
Steve Bako, Thijs Vogels, Brian McWilliams, Mark Meyer, Jan Novák, Alex Harvill, Pradeep Sen, Tony Derose, and Fabrice Rousselle · 2017
Cited alongside, same era.
Ben Mildenhall, Jonathan T Barron, Jiawen Chen, Dillon Sharlet, Ren Ng, and Robert Carroll · 2018
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Spatially-adaptive filter units for deep neural networks
Domen Tabernik, Matej Kristan, and Aleš Leonardis · 2018
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Blade: Filter learning for general purpose computational photography
Pascal Getreuer, Ignacio Garcia-Dorado, John Isidoro, Sungjoon Choi, Frank Ong, and Peyman Milanfar · 2018
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Fast, accurate, and lightweight super-resolution with cascading residual network
Namhyuk Ahn, Byungkon Kang, and Kyung-Ah Sohn · 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
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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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A fully progressive approach to single-image super-resolution
W. Yifan, F. Perazzi, B. McWilliams, A. Sorkine-Hornung, O Sorkine-Hornung, and C. Schroers · 2018
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Second-order attention network for single image super-resolution
Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, and Lei Zhang · 2019
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Meta-sr: a magnification-arbitrary network for super-resolution
Xuecai Hu, Haoyuan Mu, Xiangyu Zhang, Zilei Wang, Tieniu Tan, and Jian Sun · 2019
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Lightweight image super-resolution with adaptive weighted learning network
Chaofeng Wang, Zheng Li, and Jun Shi · 2019
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Feedback network for image super-resolution
Zhen Li, Jinglei Yang, Zheng Liu, Xiaomin Yang, Gwanggil Jeon, and Wei Wu · 2019
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Fast, accurate and lightweight super-resolution with neural architecture search
Xiangxiang Chu, Bo Zhang, Hailong Ma, Ruijun Xu, Jixiang Li, and Qingyuan Li · 2019
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Unfolding the alternating optimization for blind super resolution, 2020
Zhengxiong Luo, Yan Huang, Shang Li, Liang Wang, and Tieniu Tan · 2020
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Deep unfolding network for image super-resolution
Kai Zhang, Luc Van Gool, and Radu Timofte · 2020
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