Paper Info
Title
NTIRE 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study
Abstract
This paper introduces a novel large dataset for video de blurring, video super-resolution and studies the state-of-the-art as emerged from the NTIRE 2019 video restoration challenges. The video deblurring and video super-resolution challenges are each the first challenge of its kind, with 4 competitions, hundreds of participants and tens of proposed solutions. Our newly collected REalistic and Diverse Scenes dataset (REDS) was employed by the challenges. In our study, we compare the solutions from the challenges to a set of representative methods from the literature and evaluate them on our proposed REDS dataset. We find that the NTIRE 2019 challenges push the state-of-theart in video deblurring and super-resolution, reaching compelling performance on our newly proposed REDS dataset.
Year
DOI
Venue
2019
10.1109/CVPRW.2019.00251
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
DocType
ISSN
Citations 
Conference
2160-7508
3
PageRank 
References 
Authors
0.37
0
7
Name
Order
Citations
PageRank
Seungjun Nah140612.44
Sungyong Baik263.12
Seokil Hong392.16
Gyeongsik Moon4172.97
Sanghyun Son53409.45
Radu Timofte61880118.45
Kyoung Mu Lee73228153.84