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[paper]	https://arxiv.org/abs/1611.05250
	https://github.com/Shomlin/SuperResolutionPaperCollection#vespcn-real-time-video-super-resolution-with-spatio-temporal-networks-and-motion-compensation-cvpr-2017-paper
[paper]	http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Robust_Video_Super-Resolution_ICCV_2017_paper.html
	https://github.com/Shomlin/SuperResolutionPaperCollection#robust-video-super-resolution-with-learned-temporal-dynamics-iccv-2017-paper
	https://github.com/Shomlin/SuperResolutionPaperCollection#2016-1
[paper]	https://arxiv.org/abs/1611.07767
	https://github.com/Shomlin/SuperResolutionPaperCollection#multiframe-motion-coupling-via-infimal-convolution-regularization-for-video-super-resolution-paper
[paper]	http://ieeexplore.ieee.org/document/7444187/
	https://github.com/Shomlin/SuperResolutionPaperCollection#video-super-resolution-with-convolutional-neural-networks-paper
	https://github.com/Shomlin/SuperResolutionPaperCollection#2015-1
[paper]	https://papers.nips.cc/paper/5778-bidirectional-recurrent-convolutional-networks-for-multi-frame-super-resolution
	https://github.com/Shomlin/SuperResolutionPaperCollection#bidirectional-recurrent-convolutional-networks-for-multi-frame-super-resolution-nips-2015-paper
[paper]	http://www.cse.cuhk.edu.hk/leojia/projects/mfsr/index.html
	https://github.com/Shomlin/SuperResolutionPaperCollection#handling-motion-blur-in-multi-frame-super-resolution-paper
[paper]	http://openaccess.thecvf.com/content_iccv_2015/html/Liao_Video_Super-Resolution_via_ICCV_2015_paper.html
	https://github.com/Shomlin/SuperResolutionPaperCollection#video-super-resolution-via-deep-draft-ensemble-learning-iccv-2015-paper
	https://github.com/Shomlin/SuperResolutionPaperCollection#2011
[paper]	https://people.csail.mit.edu/celiu/CVPR2011/default.html
	https://github.com/Shomlin/SuperResolutionPaperCollection#a-bayesian-approach-to-adaptive-video-super-resolution-paper
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