NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results
METADATA ONLY
Loading...
Author / Producer
Date
2020
Publication Type
Conference Paper
ETH Bibliography
yes
Citations
Altmetric
METADATA ONLY
Data
Rights / License
Abstract
This paper reviews the NTIRE 2020 challenge on video quality mapping (VQM), which addresses the issues of quality mapping from source video domain to target video domain. The challenge includes both a supervised track (track 1) and a weakly-supervised track (track 2) for two benchmark datasets. In particular, track 1 offers a new Internet video benchmark, requiring algorithms to learn the map from more compressed videos to less compressed videos in a supervised training manner. In track 2, algorithms are required to learn the quality mapping from one device to another when their quality varies substantially and weakly- aligned video pairs are available. For track 1, in total 7 teams competed in the final test phase, demonstrating novel and effective solutions to the problem. For track 2, some existing methods are evaluated, showing promising solutions to the weakly-supervised video quality mapping problem. © 2020 IEEE.
Permanent link
Publication status
published
External links
Editor
Book title
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Journal / series
Volume
Pages / Article No.
1962 - 1974
Publisher
IEEE
Event
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2020) (virtual)