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Image downscaling and upscaling are two basic rescaling operations.
Communication in the presence of noise
Claude Elwood Shannon · 1949
Earlier work this paper cites.
Reconstruction filters in computer-graphics
Don P Mitchell and Arun N Netravali · 1988
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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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Super-resolution from a single image
Daniel Glasner, Shai Bagon, and Michal Irani · 2009
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Making a “completely blind” image quality analyzer
Anish Mittal, Rajiv Soundararajan, and Alan C Bovik · 2012
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Content-adaptive image downscaling
Johannes Kopf, Ariel Shamir, and Pieter Peers · 2013
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Nonparametric blind super-resolution
Tomer Michaeli and Michal Irani · 2013
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Nice: Non-linear independent components estimation
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Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Perceptually based downscaling of images
A Cengiz Oeztireli and Markus Gross · 2015
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Blind image quality evaluation using perception based features
N Venkatanath, D Praneeth, Maruthi Chandrasekhar Bh, Sumohana S Channappayya, and Swarup S Medasani · 2015
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 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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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
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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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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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Conditional adversarial generative flow for controllable image synthesis
Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang, and Hongsheng Li · 2019
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Pointflow: 3d point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 2019
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Learning spatial attention for face super-resolution
Chaofeng Chen, Dihong Gong, Hao Wang, Zhifeng Li, and Kwan-Yee K Wong · 2020
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Unfolding the alternating optimization for blind super resolution
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Deep feature consistent deep image transformations: Downscaling, decolorization and hdr tone mapping
Xianxu Hou, Jiang Duan, and Guoping Qiu · 2017
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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
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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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Aditya Grover, Manik Dhar, and Stefano Ermon · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Diederik P Kingma and Prafulla Dhariwal · 2018
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Learning a convolutional neural network for image compact-resolution
Yue Li, Dong Liu, Houqiang Li, Li Li, Zhu Li, and Feng Wu · 2018
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Task-aware image downscaling
Heewon Kim, Myungsub Choi, Bee Lim, and Kyoung Mu Lee
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Zhengxiong Luo, Yan Huang, Shang Li, Liang Wang, and Tieniu Tan · 2020
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C-flow: Conditional generative flow models for images and 3d point clouds
Albert Pumarola, Stefan Popov, Francesc Moreno-Noguer, and Vittorio Ferrari · 2020
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Learned image downscaling for upscaling using content adaptive resampler
Wanjie Sun and Zhenzhong Chen · 2020
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Invertible image rescaling
Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, and Tie-Yan Liu · 2020
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Adaptive super-resolution for person re-identification with low-resolution images
Ke Han, Yan Huang, Chunfeng Song, Liang Wang, and Tieniu Tan · 2021
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