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, Mingdeng Cao, Cong Heng, Lingzhi Fu, Rongyu Zhang, Yusheng Zhang, Hao Wang, Hongjian Song, Jing Wang, Haotian Fan, Xiaoxia Hou, Ming Sun, Mading Li, Kai Zhao, Kun Yuan, Zishang Kong, Mingda Wu, Chuanchuan Zheng, Marcos V. Conde, 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, Sadbhawana Thakur, Vinit Jakhetiya, Badri N Subudhi, Hao-Hsiang Yang, Hua-En Chang, Zhi-Kai Huang, Wei-Ting Chen, Sy-Yen Kuo, Saikat Dutta, Sourya Dipta Das, Nisarg A. Shah, Anil Kumar Tiwari; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022, pp. 951-967

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.

Related Material

[pdf]
[bibtex]
@InProceedings{Gu_2022_CVPR, author = {Gu, Jinjin and Cai, Haoming and Dong, Chao and Ren, Jimmy S. and Timofte, Radu and Gong, Yuan and Lao, Shanshan and Shi, Shuwei and Wang, Jiahao and Yang, Sidi and Wu, Tianhe and Xia, Weihao and Yang, Yujiu and Cao, Mingdeng and Heng, Cong and Fu, Lingzhi and Zhang, Rongyu and Zhang, Yusheng and Wang, Hao and Song, Hongjian and Wang, Jing and Fan, Haotian and Hou, Xiaoxia and Sun, Ming and Li, Mading and Zhao, Kai and Yuan, Kun and Kong, Zishang and Wu, Mingda and Zheng, Chuanchuan and Conde, Marcos V. and Burchi, Maxime and Feng, Longtao and Zhang, Tao and Li, Yang and Xu, Jingwen and Wang, Haiqiang and Liao, Yiting and Li, Junlin and Xu, Kele and Sun, Tao and Xiong, Yunsheng and Keshari, Abhisek and Komal and Thakur, Sadbhawana and Jakhetiya, Vinit and Subudhi, Badri N and Yang, Hao-Hsiang and Chang, Hua-En and Huang, Zhi-Kai and Chen, Wei-Ting and Kuo, Sy-Yen and Dutta, Saikat and Das, Sourya Dipta and Shah, Nisarg A. and Tiwari, Anil Kumar}, title = {NTIRE 2022 Challenge on Perceptual Image Quality Assessment}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2022}, pages = {951-967} }