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Most Video Super-Resolution (VSR) methods enhance a video reference frame by aligning its neighboring frames and mining information on these frames.
On bayesian adaptive video super resolution
Ce Liu and Deqing Sun · 2014
Earlier work this paper cites.
Flownet: Learning optical flow with convolutional networks
A. Dosovitskiy, P. Fischer, Eddy Ilg, Philip Häusser, Caner Hazirbas, V. Golkov, P. V. D. Smagt, D. Cremers, and T. Brox · 2015
Earlier work this paper cites.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun · 2015
Earlier work this paper cites.
Bidirectional recurrent convolutional networks for multi-frame super-resolution
Y. Huang, W. Wang, and Liang Wang · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Video super-resolution with convolutional neural networks
Armin Kappeler, Seunghwan Yoo, Qiqin Dai, and A. Katsaggelos · 2016
Earlier work this paper cites.
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
W. Shi, J. Caballero, Ferenc Huszár, J. Totz, A. Aitken, R. Bishop, D. Rueckert, and Zehan Wang · 2016
Earlier work this paper cites.
Real-time video super-resolution with spatio-temporal networks and motion compensation
J. Caballero, C. Ledig, Andrew Aitken, A. Acosta, J. Totz, Zehan Wang, and W. Shi · 2017
Earlier work this paper cites.
Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Y. Xiong, Y. Li, Guodong Zhang, H. Hu, and Y. Wei · 2017
Earlier work this paper cites.
Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
Earlier work this paper cites.
Optical flow estimation using a spatial pyramid network
A. Ranjan and Michael J. Black · 2017
Cited alongside, same era.
Detail-revealing deep video super-resolution
X. Tao, H. Gao, Renjie Liao, J. Wang, and J. Jia · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, L. Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Object detection in video with spatiotemporal sampling networks
Gedas Bertasius, L. Torresani, and J. Shi · 2018
Cited alongside, same era.
Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation
Younghyun Jo, S. Oh, Jaeyeon Kang, and S. Kim · 2018
Cited alongside, same era.
Residual dense network for image super-resolution
Yulun Zhang, Yapeng Tian, Y. Kong, B. Zhong, and Yun Fu · 2018
Cited alongside, same era.
Video enhancement with task-oriented flow
Tianfan Xue, B. Chen, Jiajun Wu, D. Wei, and W. 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, J. Jiang, and Jiayi Ma · 2019
Later among the works it cites.
Deformable convnets v2: More deformable, better results
X. Zhu, H. Hu, Stephen Lin, and Jifeng Dai · 2019
Later among the works it cites.
Basicvsr: The search for essential components in video super-resolution and beyond
Kelvin C. K. Chan, Xintao Wang, Ke Yu, C. Dong, and Chen Change Loy · 2020
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Understanding deformable alignment in video super-resolution
Kelvin C. K. Chan, Xintao Wang, K. Yu, C. Dong, and Chen Change Loy · 2020
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Recurrent back-projection network for video super-resolution
M. Haris, Gregory Shakhnarovich, and N. Ukita · 2019
Cited alongside, same era.
Sfnet: Learning object-aware semantic correspondence
J. Lee, D. Kim, J. Ponce, and Bumsub Ham · 2019
Cited alongside, same era.
Fast spatio-temporal residual network for video super-resolution
Sheng Li, Fengxiang He, B. Du, Lefei Zhang, Y. Xu, and D. Tao · 2019
Cited alongside, same era.
Edvr: Video restoration with enhanced deformable convolutional networks
Xintao Wang, Kelvin C. K. Chan, K. Yu, C. Dong, and Chen Change Loy · 2019
Cited alongside, same era.
Video super-resolution with recurrent structure-detail network
T. Isobe, Xu Jia, Shuhang Gu, Songjiang Li, Shengjin Wang, and Q. Tian · 2020
Later among the works it cites.
Video super-resolution with temporal group attention
T. Isobe, Songjiang Li, Xu Jia, Shanxin Yuan, Gregory Slabaugh, Chunjing Xu, Ya-Li Li, Shengjin Wang, and Q. Tian · 2020
Later among the works it cites.
Mucan: Multi-correspondence aggregation network for video super-resolution
Wenbo Li, Xin Tao, Taian Guo, Lu Qi, Jiangbo Lu, and Jiaya Jia · 2020
Later among the works it cites.
Tdan: Temporally-deformable alignment network for video super-resolution
Yapeng Tian, Yulun Zhang, Yun Fu, and Chenliang Xu · 2020
Later among the works it cites.
Learning texture transformer network for image super-resolution
Fuzhi Yang, Huan Yang, J. Fu, Hongtao Lu, and B. Guo · 2020
Later among the works it cites.