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Modern handheld devices can acquire burst image sequence in a quick succession.
Multiframe image restoration and registration
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Sina Farsiu, Michael Elad, and Peyman Milanfar · 2004
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Image denoising by sparse 3-d transform-domain collaborative filtering
Kostadin Dabov, A. Foi, V. Katkovnik, and K. Egiazarian · 2007
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Image super-resolution via sparse representation
Jianchao Yang, John Wright, Thomas S Huang, and Yi Ma · 2010
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M. Maggioni, G. Boracchi, A. Foi, and K. Egiazarian · 2011
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M. Maggioni, G. Boracchi, A. Foi, and K. Egiazarian · 2012
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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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Image super-resolution using deep convolutional networks
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 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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Deep networks for image super-resolution with sparse prior
Zhaowen Wang, Ding Liu, Jianchao Yang, Wei Han, and Thomas Huang · 2015
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Burst photography for high dynamic range and low-light imaging on mobile cameras
S. W. Hasinoff, Dillon Sharlet, Ryan Geiss, Andrew Adams, J. Barron, F. Kainz, Jiawen Chen, and M. Levoy · 2016
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Burst photography for high dynamic range and low-light imaging on mobile cameras
Samuel W Hasinoff, Dillon Sharlet, Ryan Geiss, Andrew Adams, Jonathan T Barron, Florian Kainz, Jiawen Chen, and Marc Levoy · 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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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 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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Dslr-quality photos on mobile devices with deep convolutional networks
Andrey Ignatov, Nikolay Kobyshev, Radu Timofte, Kenneth Vanhoey, and Luc Van Gool · 2017
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Openimages: A public dataset for large-scale multi-label and multi-class image classification
Ivan Krasin, Tom Duerig, Neil Alldrin, Vittorio Ferrari, Sami Abu-El-Haija, Alina Kuznetsova, Hassan Rom, Jasper Uijlings, Stefan Popov, Andreas Veit, Serge Belongie, Victor Gomes, Abhinav Gupta, Chen Sun, Gal Chechik, David Cai, Zheyun Feng, Dhyanesh Narayanan, and Kevin Murphy · 2017
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Deep laplacian pyramid networks for fast and accurate superresolution
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
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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
Edvr: Video restoration with enhanced deformable convolutional networks
Xintao Wang, Kelvin CK Chan, Ke Yu, Chao Dong, and Chen Change Loy · 2019
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Handheld multi-frame super-resolution
Bartlomiej Wronski, Ignacio Garcia-Dorado, Manfred Ernst, Damien Kelly, Michael Krainin, Chia-Kai Liang, Marc Levoy, and Peyman Milanfar · 2019
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End-to-end denoising of dark burst images using recurrent fully convolutional networks
Di Zhao, Lan Ma, Songnan Li, and Dahai Yu · 2019
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Deformable convnets v2: More deformable, better results
Xizhou Zhu, Han Hu, Stephen Lin, and Jifeng Dai · 2019
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A deep journey into super-resolution: A survey
Saeed Anwar, Salman Khan, and Nick Barnes · 2020
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HighRes-net: recursive fusion for multi-frame super-resolution of satellite imagery
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Enhancenet: Single image super-resolution through automated texture synthesis
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Image super-resolution via deep recursive residual network
Ying Tai, Jian Yang, and Xiaoming Liu · 2017
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Deep multi-frame face super-resolution
Evgeniya Ustinova and Victor Lempitsky · 2017
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Fast, accurate, and lightweight super-resolution with cascading residual network
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Learning to see in the dark
Chen Chen, Qifeng Chen, Jia Xu, and Vladlen Koltun · 2018
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Deep burst denoising
C. Godard, K. Matzen, and Matthew Uyttendaele · 2018
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Deep back-projection networks for super-resolution
Muhammad Haris, Gregory Shakhnarovich, and Norimichi Ukita · 2018
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Michel Deudon, Alfredo Kalaitzis, Israel Goytom, Md Rifat Arefin, Zhichao Lin, Kris Sankaran, Vincent Michalski, Samira E Kahou, Julien Cornebise, and Yoshua Bengio · 2020
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Burst photography for learning to enhance extremely dark images
Ahmet Serdar Karadeniz, Erkut Erdem, and Aykut Erdem · 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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Tdan: Temporally-deformable alignment network for video super-resolution
Yapeng Tian, Yulun Zhang, Yun Fu, and Chenliang Xu · 2020
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Basis prediction networks for effective burst denoising with large kernels
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CycleISP: real image restoration via improved data synthesis
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Learning enriched features for real image restoration and enhancement
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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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Low light image enhancement via global and local context modeling
Aditya Arora, Muhammad Haris, Syed Waqas Zamir, Munawar Hayat, Fahad Shahbaz Khan, Ling Shao, and Ming-Hsuan Yang · 2021
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Deep burst super-resolution
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Deep reparametrization of multi-frame super-resolution and denoising
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Mobile computational photography: A tour
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Lucas-kanade reloaded: End-to-end super-resolution from raw image bursts
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Multi-stage progressive image restoration
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Learning digital camera pipeline for extreme low-light imaging
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Restormer: Efficient transformer for high-resolution image restoration
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