TY - GEN
T1 - NTIRE 2022 Challenge on Stereo Image Super-Resolution
T2 - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2022)
AU - 78 authors, including
AU - Wang, Longguang
AU - Guo, Yulan
AU - Wang, Yingqian
AU - Li, Juncheng
AU - Gu, Shuhang
AU - Timofte, Radu
AU - Chen, Liangyu
AU - Chu, Xiaojie
AU - Yu, Wenqing
AU - Jin, Kai
AU - Wei, Zeqiang
AU - Guo, Sha
AU - Yang, Angulia
AU - Zhou, Xiuzhuang
AU - Guo, Guodong
AU - Dai, Bin
AU - Peng, Feiyue
AU - Xiao, Huaxin
AU - Yan, Shen
AU - Liu, Yuxiang
AU - Cai, Hanxiao
AU - Cao, Pu
AU - Nie, Yang
AU - Yang, Lu
AU - Song, Qing
AU - Hu, Xiaotao
AU - Xu, Jun
AU - Xu, Mai
AU - Jing, Junpeng
AU - Deng, Xin
AU - Xing, Qunliang
AU - Qiao, Minglang
AU - Guan, Zhenyu
AU - Guo, Wenlong
AU - Peng, Chenxu
AU - Chen, Zan
AU - Che, Junyang
AU - Li, Hao
AU - Chen, Junbin
AU - Li, Weijie
AU - Yang, Zhijing
AU - Li, Gen
AU - Li, Aijin
AU - Sun, Lei
AU - Zhang, Dafeng
AU - Liu, Shizhuo
AU - Zhang, Jiangtao
AU - Qu, Yanyun
AU - Yang, Hao-Hsiang
AU - Huang, Zhi-Kai
AU - Huang, Yulin
N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).
PY - 2022
Y1 - 2022
N2 - In this paper, we summarize the 1st NTIRE challenge on stereo image super-resolution (restoration of rich details in a pair of low-resolution stereo images) with a focus on new solutions and results. This challenge has 1 track aiming at the stereo image super-resolution problem under a standard bicubic degradation. In total, 238 participants were successfully registered, and 21 teams competed in the final testing phase. Among those participants, 20 teams successfully submitted results with PSNR (RGB) scores better than the baseline. This challenge establishes a new benchmark for stereo image SR.
AB - In this paper, we summarize the 1st NTIRE challenge on stereo image super-resolution (restoration of rich details in a pair of low-resolution stereo images) with a focus on new solutions and results. This challenge has 1 track aiming at the stereo image super-resolution problem under a standard bicubic degradation. In total, 238 participants were successfully registered, and 21 teams competed in the final testing phase. Among those participants, 20 teams successfully submitted results with PSNR (RGB) scores better than the baseline. This challenge establishes a new benchmark for stereo image SR.
UR - http://www.scopus.com/inward/record.url?scp=85131599508&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85131599508&origin=recordpage
U2 - 10.1109/CVPRW56347.2022.00105
DO - 10.1109/CVPRW56347.2022.00105
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781665487405
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 905
EP - 918
BT - Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
PB - IEEE Computer Society
Y2 - 19 June 2022 through 24 June 2022
ER -