Title
Learning for Unconstrained Space-Time Video Super-Resolution
Abstract
Recent years have seen considerable research activities devoted to video enhancement that simultaneously increases temporal frame rate and spatial resolution. However, the existing methods either fail to explore the intrinsic relationship between temporal and spatial information or lack flexibility in the choice of final temporal/spatial resolution. In this work, we propose an unconstrained space-time video super-resolution network, which can effectively exploit space-time correlation to boost performance. Moreover, it has complete freedom in adjusting the temporal frame rate and spatial resolution through the use of the optical flow technique and a generalized pixelshuffle operation. Our extensive experiments demonstrate that the proposed method not only outperforms the state-of-the-art, but also requires far fewer parameters and less running time.
Year
DOI
Venue
2022
10.1109/TBC.2021.3131875
IEEE Transactions on Broadcasting
Keywords
DocType
Volume
Space-time video super-resolution,arbitrary temporal/spatial factors,optical flow,generalized pixelshuffle layer
Journal
68
Issue
ISSN
Citations 
2
0018-9316
1
PageRank 
References 
Authors
0.36
23
7
Name
Order
Citations
PageRank
Zhihao Shi110.70
Xiaohong Liu2114.33
Chengqi Li310.36
Linhui Dai410.36
Jun Chen573094.14
Timothy N. Davidson654257.07
Jiying Zhao710.70