TY - GEN
T1 - NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video
T2 - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2022)
AU - 79 authors, including
AU - Yang, Ren
AU - Timofte, Radu
AU - Zheng, Meisong
AU - Xing, Qunliang
AU - Qiao, Minglang
AU - Xu, Mai
AU - Jiang, Lai
AU - Liu, Huaida
AU - Chen, Ying
AU - Ben, Youcheng
AU - Zhou, Xiao
AU - Fu, Chen
AU - Cheng, Pei
AU - Yu, Gang
AU - Li, Junyi
AU - Wu, Renlong
AU - Zhang, Zhilu
AU - Shang, Wei
AU - Lv, Zhengyao
AU - Chen, Yunjin
AU - Zhou, Mingcai
AU - Ren, Dongwei
AU - Zhang, Kai
AU - Zuo, Wangmeng
AU - Ostyakov, Pavel
AU - Dmitry, Vyal
AU - Soltanayev, Shakarim
AU - Sergey, Chervontsev
AU - Magauiya, Zhussip
AU - Zou, Xueyi
AU - Yan, Youliang
AU - Navarrete Michelini, Pablo
AU - Lu, Yunhua
AU - Zhang, Diankai
AU - Liu, Shaoli
AU - Gao, Si
AU - Wu, Biao
AU - Zheng, Chengjian
AU - Zhang, Xiaofeng
AU - Lu, Kaidi
AU - Wang, Ning
AU - Nguyen Canh, Thuong
AU - Bach, Thong
AU - Wang, Qing
AU - Sun, Xiaopeng
AU - Ma, Haoyu
AU - Zhao, Shijie
AU - Li, Junlin
AU - Xie, Liangbin
AU - Shi, Shuwei
AU - Huang, Yulin
AU - Chen, Junying
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 - This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the LDV dataset (240 videos) and 95 additional videos. This challenge includes three tracks. Track 1 aims at enhancing the videos compressed by HEVC at a fixed QP. Track 2 and Track 3 target both the super-resolution and quality enhancement of HEVC compressed video. They require x2 and x4 super-resolution, respectively. The three tracks totally attract more than 600 registrations. In the test phase, 8 teams, 8 teams and 12 teams submitted the final results to Tracks 1, 2 and 3, respectively. The proposed methods and solutions gauge the state-of-the-art of super-resolution and quality enhancement of compressed video. The proposed LDV 2.0 dataset is available at https://github.com/RenYang-home/LDV_dataset. The homepage of this challenge (including open-sourced codes) is at https://github.com/RenYang-home/NTIRE22_VEnh_SR.
AB - This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the LDV dataset (240 videos) and 95 additional videos. This challenge includes three tracks. Track 1 aims at enhancing the videos compressed by HEVC at a fixed QP. Track 2 and Track 3 target both the super-resolution and quality enhancement of HEVC compressed video. They require x2 and x4 super-resolution, respectively. The three tracks totally attract more than 600 registrations. In the test phase, 8 teams, 8 teams and 12 teams submitted the final results to Tracks 1, 2 and 3, respectively. The proposed methods and solutions gauge the state-of-the-art of super-resolution and quality enhancement of compressed video. The proposed LDV 2.0 dataset is available at https://github.com/RenYang-home/LDV_dataset. The homepage of this challenge (including open-sourced codes) is at https://github.com/RenYang-home/NTIRE22_VEnh_SR.
UR - http://www.scopus.com/inward/record.url?scp=85129514553&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85129514553&origin=recordpage
U2 - 10.1109/CVPRW56347.2022.00129
DO - 10.1109/CVPRW56347.2022.00129
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781665487405
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 1220
EP - 1237
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 -