NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

Ren Yang; Radu Timofte; Meisong Zheng; Qunliang Xing; Minglang Qiao; Mai Xu; Lai Jiang; Huaida Liu; Ying Chen; Youcheng Ben; Xiao Zhou; Chen Fu; Pei Cheng; Gang Yu; Junyi Li; Renlong Wu; Zhilu Zhang; Wei Shang; Zhengyao Lv; Yunjin Chen; Mingcai Zhou; Dongwei Ren; Kai Zhang; Wangmeng Zuo; Pavel Ostyakov; Vyal Dmitry; Shakarim Soltanayev; Chervontsev Sergey; Zhussip Magauiya; Xueyi Zou; Youliang Yan; Pablo Navarrete Michelini; Yunhua Lu; Diankai Zhang; Shaoli Liu; Si Gao; Biao Wu; Chengjian Zheng; Xiaofeng Zhang; Kaidi Lu; Ning Wang; Thuong Nguyen Canh; Thong Bach; Qing Wang; Xiaopeng Sun; Haoyu Ma; Shijie Zhao; Junlin Li; Liangbin Xie; Shuwei Shi; Yujiu Yang; Xintao Wang; Jinjin Gu; Chao Dong; Xiaodi Shi; Chunmei Nian; Dong Jiang; Jucai Lin; Zhihuai Xie; Mao Ye; Dengyan Luo; Liuhan Peng; Shengjie Chen; Xin Liu; Qian Wang; Xin Liu; Boyang Liang; Hang Dong; Yuhao Huang; Kai Chen; Xingbei Guo; Yujing Sun; Huilei Wu; Pengxu Wei; Yulin Huang; Junying Chen; Ik Hyun Lee; Sunder Ali Khowaja; Jiseok Yoon

doi:10.1109/CVPRW56347.2022.00129

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

Ren Yang
, Radu Timofte
, Meisong Zheng
, Qunliang Xing
, Minglang Qiao
, Mai Xu
, Lai Jiang
, Huaida Liu
, Ying Chen
, Youcheng Ben
, Xiao Zhou
, Chen Fu
, Pei Cheng
, Gang Yu
, Junyi Li
, Renlong Wu
, Zhilu Zhang
, Wei Shang
, Zhengyao Lv
, Yunjin Chen

Mingcai Zhou, Dongwei Ren, Kai Zhang, Wangmeng Zuo, Pavel Ostyakov, Vyal Dmitry, Shakarim Soltanayev, Chervontsev Sergey, Zhussip Magauiya, Xueyi Zou, Youliang Yan, Pablo Navarrete Michelini, Yunhua Lu, Diankai Zhang, Shaoli Liu, Si Gao, Biao Wu, Chengjian Zheng, Xiaofeng Zhang, Kaidi Lu, Ning Wang, Thuong Nguyen Canh, Thong Bach, Qing Wang, Xiaopeng Sun, Haoyu Ma, Shijie Zhao, Junlin Li, Liangbin Xie, Shuwei Shi, Yujiu Yang, Xintao Wang, Jinjin Gu, Chao Dong, Xiaodi Shi, Chunmei Nian, Dong Jiang, Jucai Lin, Zhihuai Xie, Mao Ye, Dengyan Luo, Liuhan Peng, Shengjie Chen, Xin Liu, Qian Wang, Xin Liu, Boyang Liang, Hang Dong, Yuhao Huang, Kai Chen, Xingbei Guo, Yujing Sun, Huilei Wu, Pengxu Wei, Yulin Huang, Junying Chen, Ik Hyun Lee, Sunder Ali Khowaja, Jiseok Yoon

ETH Zurich
University of Würzburg
Beihang University
Tencent
Harbin Institute of Technology
Huawei Technologies Co., Ltd.
Boe Technology Group
ZTE Corporation
The University of Osaka
ByteDance Ltd.
Shanghai Artificial Intelligence Laboratory
Shenzhen Institute of Advanced Technology
Hangzhou Dianzi University
University of Electronic Science and Technology of China
Xinjiang University
Peking University
China Mobile Research Institute
City University of Hong Kong
Sun Yat-Sen University
South China University of Technology
Tech University of Korea
Iklab
University of Sindh

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

33 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Publisher	IEEE Computer Society
Pages	1220-1237
Number of pages	18
ISBN (Electronic)	9781665487399
DOIs	https://doi.org/10.1109/CVPRW56347.2022.00129
State	Published - 2022
Externally published	Yes
Event	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 - New Orleans, United States Duration: 19 Jun 2022 → 24 Jun 2022

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2022-June
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Country/Territory	United States
City	New Orleans
Period	19/06/22 → 24/06/22

Access to Document

10.1109/CVPRW56347.2022.00129

Cite this

Yang, R., Timofte, R., Zheng, M., Xing, Q., Qiao, M., Xu, M., Jiang, L., Liu, H., Chen, Y., Ben, Y., Zhou, X., Fu, C., Cheng, P., Yu, G., Li, J., Wu, R., Zhang, Z., Shang, W., Lv, Z., ... Yoon, J. (2022). NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 (pp. 1220-1237). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW56347.2022.00129

Yang, Ren ; Timofte, Radu ; Zheng, Meisong et al. / NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video : Dataset, Methods and Results. Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society, 2022. pp. 1220-1237 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

@inproceedings{ce48238d8e6347bd95fec6b26748d96e,

title = "NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results",

abstract = "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.",

author = "Ren Yang and Radu Timofte and Meisong Zheng and Qunliang Xing and Minglang Qiao and Mai Xu and Lai Jiang and Huaida Liu and Ying Chen and Youcheng Ben and Xiao Zhou and Chen Fu and Pei Cheng and Gang Yu and Junyi Li and Renlong Wu and Zhilu Zhang and Wei Shang and Zhengyao Lv and Yunjin Chen and Mingcai Zhou and Dongwei Ren and Kai Zhang and Wangmeng Zuo and Pavel Ostyakov and Vyal Dmitry and Shakarim Soltanayev and Chervontsev Sergey and Zhussip Magauiya and Xueyi Zou and Youliang Yan and \{Navarrete Michelini\}, Pablo and Yunhua Lu and Diankai Zhang and Shaoli Liu and Si Gao and Biao Wu and Chengjian Zheng and Xiaofeng Zhang and Kaidi Lu and Ning Wang and \{Nguyen Canh\}, Thuong and Thong Bach and Qing Wang and Xiaopeng Sun and Haoyu Ma and Shijie Zhao and Junlin Li and Liangbin Xie and Shuwei Shi and Yujiu Yang and Xintao Wang and Jinjin Gu and Chao Dong and Xiaodi Shi and Chunmei Nian and Dong Jiang and Jucai Lin and Zhihuai Xie and Mao Ye and Dengyan Luo and Liuhan Peng and Shengjie Chen and Xin Liu and Qian Wang and Xin Liu and Boyang Liang and Hang Dong and Yuhao Huang and Kai Chen and Xingbei Guo and Yujing Sun and Huilei Wu and Pengxu Wei and Yulin Huang and Junying Chen and \{Hyun Lee\}, Ik and \{Ali Khowaja\}, Sunder and Jiseok Yoon",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 ; Conference date: 19-06-2022 Through 24-06-2022",

year = "2022",

doi = "10.1109/CVPRW56347.2022.00129",

language = "英语",

series = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",

publisher = "IEEE Computer Society",

pages = "1220--1237",

booktitle = "Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022",

address = "美国",

}

Yang, R, Timofte, R, Zheng, M, Xing, Q, Qiao, M, Xu, M, Jiang, L, Liu, H, Chen, Y, Ben, Y, Zhou, X, Fu, C, Cheng, P, Yu, G, Li, J, Wu, R, Zhang, Z, Shang, W, Lv, Z, Chen, Y, Zhou, M, Ren, D, Zhang, K, Zuo, W, Ostyakov, P, Dmitry, V, Soltanayev, S, Sergey, C, Magauiya, Z, Zou, X, Yan, Y, Navarrete Michelini, P, Lu, Y, Zhang, D, Liu, S, Gao, S, Wu, B, Zheng, C, Zhang, X, Lu, K, Wang, N, Nguyen Canh, T, Bach, T, Wang, Q, Sun, X, Ma, H, Zhao, S, Li, J, Xie, L, Shi, S, Yang, Y, Wang, X, Gu, J, Dong, C, Shi, X, Nian, C, Jiang, D, Lin, J, Xie, Z, Ye, M, Luo, D, Peng, L, Chen, S, Liu, X, Wang, Q, Liu, X, Liang, B, Dong, H, Huang, Y, Chen, K, Guo, X, Sun, Y, Wu, H, Wei, P, Huang, Y, Chen, J, Hyun Lee, I, Ali Khowaja, S & Yoon, J 2022, NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results. in Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2022-June, IEEE Computer Society, pp. 1220-1237, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022, New Orleans, United States, 19/06/22. https://doi.org/10.1109/CVPRW56347.2022.00129

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results. / Yang, Ren; Timofte, Radu; Zheng, Meisong et al.
Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society, 2022. p. 1220-1237 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 - 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 - Yang, Yujiu

AU - Wang, Xintao

AU - Gu, Jinjin

AU - Dong, Chao

AU - Shi, Xiaodi

AU - Nian, Chunmei

AU - Jiang, Dong

AU - Lin, Jucai

AU - Xie, Zhihuai

AU - Ye, Mao

AU - Luo, Dengyan

AU - Peng, Liuhan

AU - Chen, Shengjie

AU - Liu, Xin

AU - Wang, Qian

AU - Liu, Xin

AU - Liang, Boyang

AU - Dong, Hang

AU - Huang, Yuhao

AU - Chen, Kai

AU - Guo, Xingbei

AU - Sun, Yujing

AU - Wu, Huilei

AU - Wei, Pengxu

AU - Huang, Yulin

AU - Chen, Junying

AU - Hyun Lee, Ik

AU - Ali Khowaja, Sunder

AU - Yoon, Jiseok

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 - https://www.scopus.com/pages/publications/85129514553

U2 - 10.1109/CVPRW56347.2022.00129

DO - 10.1109/CVPRW56347.2022.00129

M3 - 会议稿件

AN - SCOPUS:85129514553

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 -

Yang R, Timofte R, Zheng M, Xing Q, Qiao M, Xu M et al. NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society. 2022. p. 1220-1237. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW56347.2022.00129

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

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