NTIRE 2022 Challenge on Perceptual Image Quality Assessment

Jinjin Gu; Haoming Cai; Chao Dong; Jimmy S. Ren; Radu Timofte; Yuan Gong; Shanshan Lao; Shuwei Shi; Jiahao Wang; Sidi Yang; Tianhe Wu; Weihao Xia; Yujiu Yang; Cong Heng; Lingzhi Fu; Rongyu Zhang; Yusheng Zhang; Hao Wang; Hongjian Song; Jing Wang; Ming Sun; Mading Li; Kai Zhao; Kun Yuan; Zishang Kong; Mingda Wu; Chuanchuan Zheng; Maxime Burchi; Longtao Feng; Tao Zhang; Yang Li; Jingwen Xu; Haiqiang Wang; Yiting Liao; Junlin Li; Kele Xu; Tao Sun; Yunsheng Xiong; Abhisek Keshari; Komal Komal; Sadbhawana Thakur; Vinit Jakhetiya; Badri N. Subudhi; Saikat Dutta; Sourya Dipta Das; Nisarg A. Shah; Anil Kumar Tiwari; Sidi Yang; Tianhe Wu; Shuwei Shi; Shanshan Lao; Yuan Gong; Mingdeng Cao; Jiahao Wang; Yujiu Yang; Jing Wang; Haotian Fan; Xiaoxia Hou; Marcos V. Conde; Maxime Burchi; Ming Sun; Mading Li; Kai Zhao; Kun Yuan; Zishang Kong; Mingda Wu; Chuanchuan Zheng; Heng Cong; Lingzhi Fu; Rongyu Zhang; Yusheng Zhang; Hao Wang; Hongjian Song; Hao Hsiang Yang; Hua En Chang; Zhi Kai Huang; Wei Ting Chen; Sy Yen Kuo

doi:10.1109/CVPRW56347.2022.00109

NTIRE 2022 Challenge on Perceptual Image Quality Assessment

Jinjin Gu
, Haoming Cai
, Chao Dong
, Jimmy S. Ren
, Radu Timofte
, Yuan Gong
, Shanshan Lao
, Shuwei Shi
, Jiahao Wang
, Sidi Yang
, Tianhe Wu
, Weihao Xia
, Yujiu Yang
, Cong Heng
, Lingzhi Fu
, Rongyu Zhang
, Yusheng Zhang
, Hao Wang
, Hongjian Song
, Jing Wang

Ming Sun, Mading Li, Kai Zhao, Kun Yuan, Zishang Kong, Mingda Wu, Chuanchuan Zheng, Maxime Burchi, Longtao Feng, Tao Zhang, Yang Li, Jingwen Xu, Haiqiang Wang, Yiting Liao, Junlin Li, Kele Xu, Tao Sun, Yunsheng Xiong, Abhisek Keshari, Komal Komal, Sadbhawana Thakur, Vinit Jakhetiya, Badri N. Subudhi, Saikat Dutta, Sourya Dipta Das, Nisarg A. Shah, Anil Kumar Tiwari, Sidi Yang, Tianhe Wu, Shuwei Shi, Shanshan Lao, Yuan Gong, Mingdeng Cao, Jiahao Wang, Yujiu Yang, Jing Wang, Haotian Fan, Xiaoxia Hou, Marcos V. Conde, Maxime Burchi, Ming Sun, Mading Li, Kai Zhao, Kun Yuan, Zishang Kong, Mingda Wu, Chuanchuan Zheng, Heng Cong, Lingzhi Fu, Rongyu Zhang, Yusheng Zhang, Hao Wang, Hongjian Song, Hao Hsiang Yang, Hua En Chang, Zhi Kai Huang, Wei Ting Chen, Sy Yen Kuo

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

72 Citations (Scopus)

Abstract

This paper reports on the NTIRE 2022 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2022. This challenge is held to address the emerging challenge of IQA by perceptual image processing algorithms. The output images of these algorithms have completely different characteristics from traditional distortions and are included in the PIPAL dataset used in this challenge. This challenge is divided into two tracks, a full-reference IQA track similar to the previous NTIRE IQA challenge and a new track that focuses on the no-reference IQA methods. The challenge has 192 and 179 registered participants for two tracks. In the final testing stage, 7 and 8 participating teams submitted their models and fact sheets. Almost all of them have achieved better results than existing IQA methods, and the winning method can demonstrate state-of-the-art performance.

Original language	English
Title of host publication	Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Pages	950-966
Number of pages	17
ISBN (Electronic)	9781665487399
DOIs	https://doi.org/10.1109/CVPRW56347.2022.00109
Publication status	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/CVPRW56347.2022.00109

Cite this

Gu, J., Cai, H., Dong, C., Ren, J. S., Timofte, R., Gong, Y., Lao, S., Shi, S., Wang, J., Yang, S., Wu, T., Xia, W., Yang, Y., Heng, C., Fu, L., Zhang, R., Zhang, Y., Wang, H., Song, H., ... Kuo, S. Y. (2022). NTIRE 2022 Challenge on Perceptual Image Quality Assessment. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 (pp. 950-966). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June). https://doi.org/10.1109/CVPRW56347.2022.00109

@inproceedings{9d1227186f444446825f88f6629ee76e,

title = "NTIRE 2022 Challenge on Perceptual Image Quality Assessment",

abstract = "This paper reports on the NTIRE 2022 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2022. This challenge is held to address the emerging challenge of IQA by perceptual image processing algorithms. The output images of these algorithms have completely different characteristics from traditional distortions and are included in the PIPAL dataset used in this challenge. This challenge is divided into two tracks, a full-reference IQA track similar to the previous NTIRE IQA challenge and a new track that focuses on the no-reference IQA methods. The challenge has 192 and 179 registered participants for two tracks. In the final testing stage, 7 and 8 participating teams submitted their models and fact sheets. Almost all of them have achieved better results than existing IQA methods, and the winning method can demonstrate state-of-the-art performance.",

author = "Jinjin Gu and Haoming Cai and Chao Dong and Ren, \{Jimmy S.\} and Radu Timofte and Yuan Gong and Shanshan Lao and Shuwei Shi and Jiahao Wang and Sidi Yang and Tianhe Wu and Weihao Xia and Yujiu Yang and Cong Heng and Lingzhi Fu and Rongyu Zhang and Yusheng Zhang and Hao Wang and Hongjian Song and Jing Wang and Ming Sun and Mading Li and Kai Zhao and Kun Yuan and Zishang Kong and Mingda Wu and Chuanchuan Zheng and Maxime Burchi and Longtao Feng and Tao Zhang and Yang Li and Jingwen Xu and Haiqiang Wang and Yiting Liao and Junlin Li and Kele Xu and Tao Sun and Yunsheng Xiong and Abhisek Keshari and Komal Komal and Sadbhawana Thakur and Vinit Jakhetiya and Subudhi, \{Badri N.\} and Saikat Dutta and Das, \{Sourya Dipta\} and Shah, \{Nisarg A.\} and Tiwari, \{Anil Kumar\} and Sidi Yang and Tianhe Wu and Shuwei Shi and Shanshan Lao and Yuan Gong and Mingdeng Cao and Jiahao Wang and Yujiu Yang and Jing Wang and Haotian Fan and Xiaoxia Hou and Conde, \{Marcos V.\} and Maxime Burchi and Ming Sun and Mading Li and Kai Zhao and Kun Yuan and Zishang Kong and Mingda Wu and Chuanchuan Zheng and Heng Cong and Lingzhi Fu and Rongyu Zhang and Yusheng Zhang and Hao Wang and Hongjian Song and Yang, \{Hao Hsiang\} and Chang, \{Hua En\} and Huang, \{Zhi Kai\} and Chen, \{Wei Ting\} and Kuo, \{Sy Yen\}",

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/CVPRW56347.2022.00109",

language = "English",

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

pages = "950--966",

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

}

Gu, J, Cai, H, Dong, C, Ren, JS, Timofte, R, Gong, Y, Lao, S, Shi, S, Wang, J, Yang, S, Wu, T, Xia, W, Yang, Y, Heng, C, Fu, L, Zhang, R, Zhang, Y, Wang, H, Song, H, Wang, J, Sun, M, Li, M, Zhao, K, Yuan, K, Kong, Z, Wu, M, Zheng, C, Burchi, M, Feng, L, Zhang, T, Li, Y, Xu, J, Wang, H, Liao, Y, Li, J, Xu, K, Sun, T, Xiong, Y, Keshari, A, Komal, K, Thakur, S, Jakhetiya, V, Subudhi, BN, Dutta, S, Das, SD, Shah, NA, Tiwari, AK, Yang, S, Wu, T, Shi, S, Lao, S, Gong, Y, Cao, M, Wang, J, Yang, Y, Wang, J, Fan, H, Hou, X, Conde, MV, Burchi, M, Sun, M, Li, M, Zhao, K, Yuan, K, Kong, Z, Wu, M, Zheng, C, Cong, H, Fu, L, Zhang, R, Zhang, Y, Wang, H, Song, H, Yang, HH, Chang, HE, Huang, ZK, Chen, WT & Kuo, SY 2022, NTIRE 2022 Challenge on Perceptual Image Quality Assessment. 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, pp. 950-966, 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/CVPRW56347.2022.00109

NTIRE 2022 Challenge on Perceptual Image Quality Assessment. / Gu, Jinjin; Cai, Haoming; Dong, Chao et al.
Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. 2022. p. 950-966 (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 Perceptual Image Quality Assessment

AU - Gu, Jinjin

AU - Cai, Haoming

AU - Dong, Chao

AU - Ren, Jimmy S.

AU - Timofte, Radu

AU - Gong, Yuan

AU - Lao, Shanshan

AU - Shi, Shuwei

AU - Wang, Jiahao

AU - Yang, Sidi

AU - Wu, Tianhe

AU - Xia, Weihao

AU - Yang, Yujiu

AU - Heng, Cong

AU - Fu, Lingzhi

AU - Zhang, Rongyu

AU - Zhang, Yusheng

AU - Wang, Hao

AU - Song, Hongjian

AU - Wang, Jing

AU - Sun, Ming

AU - Li, Mading

AU - Zhao, Kai

AU - Yuan, Kun

AU - Kong, Zishang

AU - Wu, Mingda

AU - Zheng, Chuanchuan

AU - Burchi, Maxime

AU - Feng, Longtao

AU - Zhang, Tao

AU - Li, Yang

AU - Xu, Jingwen

AU - Wang, Haiqiang

AU - Liao, Yiting

AU - Li, Junlin

AU - Xu, Kele

AU - Sun, Tao

AU - Xiong, Yunsheng

AU - Keshari, Abhisek

AU - Komal, Komal

AU - Thakur, Sadbhawana

AU - Jakhetiya, Vinit

AU - Subudhi, Badri N.

AU - Dutta, Saikat

AU - Das, Sourya Dipta

AU - Shah, Nisarg A.

AU - Tiwari, Anil Kumar

AU - Yang, Sidi

AU - Wu, Tianhe

AU - Shi, Shuwei

AU - Lao, Shanshan

AU - Gong, Yuan

AU - Cao, Mingdeng

AU - Wang, Jiahao

AU - Yang, Yujiu

AU - Wang, Jing

AU - Fan, Haotian

AU - Hou, Xiaoxia

AU - Conde, Marcos V.

AU - Burchi, Maxime

AU - Sun, Ming

AU - Li, Mading

AU - Zhao, Kai

AU - Yuan, Kun

AU - Kong, Zishang

AU - Wu, Mingda

AU - Zheng, Chuanchuan

AU - Cong, Heng

AU - Fu, Lingzhi

AU - Zhang, Rongyu

AU - Zhang, Yusheng

AU - Wang, Hao

AU - Song, Hongjian

AU - Yang, Hao Hsiang

AU - Chang, Hua En

AU - Huang, Zhi Kai

AU - Chen, Wei Ting

AU - Kuo, Sy Yen

PY - 2022

Y1 - 2022

N2 - This paper reports on the NTIRE 2022 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2022. This challenge is held to address the emerging challenge of IQA by perceptual image processing algorithms. The output images of these algorithms have completely different characteristics from traditional distortions and are included in the PIPAL dataset used in this challenge. This challenge is divided into two tracks, a full-reference IQA track similar to the previous NTIRE IQA challenge and a new track that focuses on the no-reference IQA methods. The challenge has 192 and 179 registered participants for two tracks. In the final testing stage, 7 and 8 participating teams submitted their models and fact sheets. Almost all of them have achieved better results than existing IQA methods, and the winning method can demonstrate state-of-the-art performance.

AB - This paper reports on the NTIRE 2022 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2022. This challenge is held to address the emerging challenge of IQA by perceptual image processing algorithms. The output images of these algorithms have completely different characteristics from traditional distortions and are included in the PIPAL dataset used in this challenge. This challenge is divided into two tracks, a full-reference IQA track similar to the previous NTIRE IQA challenge and a new track that focuses on the no-reference IQA methods. The challenge has 192 and 179 registered participants for two tracks. In the final testing stage, 7 and 8 participating teams submitted their models and fact sheets. Almost all of them have achieved better results than existing IQA methods, and the winning method can demonstrate state-of-the-art performance.

UR - https://www.scopus.com/pages/publications/85129534384

U2 - 10.1109/CVPRW56347.2022.00109

DO - 10.1109/CVPRW56347.2022.00109

M3 - Conference contribution

AN - SCOPUS:85129534384

T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

SP - 950

EP - 966

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

T2 - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022

Y2 - 19 June 2022 through 24 June 2022

ER -

NTIRE 2022 Challenge on Perceptual Image Quality Assessment

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