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Video super-resolution (VSR) approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension.
Two deterministic half-quadratic regularization algorithms for computed imaging
Pierre Charbonnier, Laure Blanc-Feraud, Gilles Aubert, and Michel Barlaud · 1994
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Understanding deformable alignment in video super-resolution
Kelvin CK Chan, Xintao Wang, Ke Yu, Chao Dong, and Chen Change Loy · 2009
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Super-resolution without explicit subpixel motion estimation
Hiroyuki Takeda, Peyman Milanfar, Matan Protter, and Michael Elad · 2009
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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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On bayesian adaptive video super resolution
Ce Liu and Deqing Sun · 2014
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Bidirectional recurrent convolutional networks for multi-frame super-resolution
Yan Huang, Wei Wang, and Liang Wang · 2015
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2015
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Image super-resolution using deep convolutional networks
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2016
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SGDR: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Clockwork convnets for video semantic segmentation
Evan Shelhamer, Kate Rakelly, Judy Hoffman, and Trevor Darrell · 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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Real-time video super-resolution with spatio-temporal networks and motion compensation
Jose Caballero, Christian Ledig, Aitken Andrew, Acosta Alejandro, Johannes Totz, Zehan Wang, and Wenzhe Shi · 2017
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 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
Cited alongside, same era.
Optical flow estimation using a spatial pyramid network
Anurag Ranjan and Michael J Black · 2017
Cited alongside, same era.
Detail-revealing deep video super-resolution
Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, and Jiaya Jia · 2017
Cited alongside, same era.
FAST: A framework to accelerate super-resolution processing on compressed videos
Zhengdong Zhang and Vivienne Sze · 2017
Cited alongside, same era.
Flow-guided feature aggregation for video object detection
Xizhou Zhu, Yujie Wang, Jifeng Dai, Lu Yuan, and Yichen Wei · 2017
Cited alongside, same era.
Deep feature flow for video recognition
Xizhou Zhu, Yuwen Xiong, Jifeng Dai, Lu Yuan, and Yichen Wei · 2017
Cited alongside, same era.
Recurrent back-projection network for video super-resolution
Muhammad Haris, Greg Shakhnarovich, and Norimichi Ukita · 2019
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Accel: A corrective fusion network for efficient semantic segmentation on video
Samvit Jain, Xin Wang, and Joseph E Gonzalez · 2019
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NTIRE 2019 challenge on video deblurring and super-resolution: Dataset and study
Seungjun Nah, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Radu Timofte, and Kyoung Mu Lee · 2019
Later among the works it cites.
Deformable non-local network for video super-resolution
Hua Wang, Dewei Su, Chuangchuang Liu, Longcun Jin, Xianfang Sun, and Xinyi Peng · 2019
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EDVR: Video restoration with enhanced deformable convolutional networks
Xintao Wang, Kelvin C.K. Chan, Ke Yu, Chao Dong, and Chen Change Loy · 2019
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Video enhancement with task-oriented flow
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Optimizing video object detection via a scale-time lattice
Kai Chen, Jiaqi Wang, Shuo Yang, Xingcheng Zhang, Yuanjun Xiong, Chen Change Loy, and Dahua Lin · 2018
Cited alongside, same era.
Video super-resolution via bidirectional recurrent convolutional networks
Yan Huang, Wei Wang, and Liang Wang · 2018
Cited alongside, same era.
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
Cited alongside, same era.
Spatio-temporal transformer network for video restoration
Tae Hyun Kim, Mehdi S M Sajjadi, Michael Hirsch, and Bernhard Schölkopf · 2018
Cited alongside, same era.
Frame-recurrent video super-resolution
Mehdi S M Sajjadi, Raviteja Vemulapalli, and Matthew Brown · 2018
Cited alongside, same era.
Towards high performance video object detection for mobiles
Xizhou Zhu, Jifeng Dai, Xingchi Zhu, Yichen Wei, and Lu Yuan · 2018
Cited alongside, same era.
Tianfan Xue, Baian Chen, Jiajun Wu, Donglai Wei, and William T Freeman · 2019
Later among the works it cites.
Progressive fusion video super-resolution network via exploiting non-local spatio-temporal correlations
Peng Yi, Zhongyuan Wang, Kui Jiang, Junjun Jiang, and Jiayi Ma · 2019
Later among the works it cites.
Deformable convnets v2: More deformable, better results
Xizhou Zhu, Han Hu, Stephen Lin, and Jifeng Dai · 2019
Later among the works it cites.
Video super-resolution with recurrent structure-detail network
Takashi Isobe, Xu Jia, Shuhang Gu, Songjiang Li, Shengjin Wang, and Qi Tian · 2020
Closest in time.
Video super-resolution with temporal group attention
Takashi Isobe, Songjiang Li, Xu Jia, Shanxin Yuan, Gregory Slabaugh, Chunjing Xu, Ya-Li Li, Shengjin Wang, and Qi Tian · 2020
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Revisiting temporal modeling for video super-resolution
Takashi Isobe, Fang Zhu, and Shengjin Wang · 2020
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MuCAN: Multi-correspondence aggregation network for video super-resolution
Wenbo Li, Xin Tao, Taian Guo, Lu Qi, Jiangbo Lu, and Jiaya Jia · 2020
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TDAN: Temporally deformable alignment network for video super-resolution
Yapeng Tian, Yulun Zhang, Yun Fu, and Chenliang Xu · 2020
Closest in time.