Learning for Video Super-Resolution through HR Optical Flow Estimation

23 September 2018

Papers citing "Learning for Video Super-Resolution through HR Optical Flow Estimation"

8 / 8 papers shown

Title
You Only Align Once: Bidirectional Interaction for Spatial-Temporal Video Super-Resolution Mengshun Hu Kui Jiang Zhixiang Nie Zheng Wang 25 20 0 13 Jul 2022
RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution Z. Geng Luming Liang Tianyu Ding Ilya Zharkov 21 68 0 27 Mar 2022
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling Hongying Liu Peng Zhao Zhubo Ruan Fanhua Shang Yuanyuan Liu SupR 24 24 0 22 Mar 2021
A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution Hongying Liu Zhubo Ruan Chaowei Fang Peng Zhao Fanhua Shang Yuanyuan Liu Lijun Wang 24 17 0 24 Aug 2020
Video Super Resolution Based on Deep Learning: A Comprehensive Survey Hongying Liu Zhubo Ruan Peng Zhao Chao Dong Fanhua Shang Yuanyuan Liu Linlin Yang Radu Timofte SupR 20 167 0 25 Jul 2020
Deep Video Super-Resolution using HR Optical Flow Estimation Longguang Wang Yulan Guo Li Liu Zaiping Lin Xinpu Deng W. An SupR 33 138 0 06 Jan 2020
Learning Parallax Attention for Stereo Image Super-Resolution Longguang Wang Yingqian Wang Zhengfa Liang Zaiping Lin Jungang Yang W. An Yulan Guo SupR 18 249 0 14 Mar 2019
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi Jose Caballero Ferenc Huszár J. Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang SupR 190 5,173 0 16 Sep 2016