Abstract | ||
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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. |
Year | DOI | Venue |
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2022 | 10.1109/CVPRW56347.2022.00109 | IEEE Conference on Computer Vision and Pattern Recognition |
DocType | Volume | Issue |
Conference | 2022 | 1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
56 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jinjin Gu | 1 | 35 | 6.89 |
Haoming Cai | 2 | 4 | 1.74 |
Chao Dong | 3 | 2064 | 80.72 |
Jimmy S. J. Ren | 4 | 324 | 23.85 |
Radu Timofte | 5 | 1880 | 118.45 |
Yuan Gong | 6 | 0 | 0.34 |
Shanshan Lao | 7 | 0 | 0.68 |
Shuwei Shi | 8 | 0 | 0.34 |
Jiahao Wang | 9 | 0 | 0.34 |
Sidi Yang | 10 | 0 | 1.01 |
Tianhe Wu | 11 | 0 | 1.01 |
Weihao Xia | 12 | 0 | 0.34 |
Yang Yu-Jiu | 13 | 89 | 19.30 |
Mingdeng Cao | 14 | 0 | 0.34 |
Cong Heng | 15 | 0 | 0.34 |
Lingzhi Fu | 16 | 0 | 0.68 |
Rongyu Zhang | 17 | 0 | 0.34 |
Yusheng Zhang | 18 | 0 | 0.34 |
Hao Wang | 19 | 0 | 0.34 |
Hongjian Song | 20 | 0 | 0.34 |
Jing Wang | 21 | 28 | 23.94 |
Haotian Fan | 22 | 0 | 0.34 |
Xiaoxia Hou | 23 | 0 | 0.34 |
Ming Sun | 24 | 0 | 0.34 |
Mading Li | 25 | 0 | 0.34 |
Kai Zhao | 26 | 0 | 0.34 |
Kun Yuan | 27 | 0 | 0.34 |
Zishang Kong | 28 | 0 | 0.34 |
Mingda Wu | 29 | 0 | 0.34 |
Chuanchuan Zheng | 30 | 0 | 0.34 |
Marcos V. Conde | 31 | 0 | 0.34 |
Maxime Burchi | 32 | 0 | 0.34 |
Longtao Feng | 33 | 0 | 0.34 |
Tao Zhang | 34 | 422 | 100.57 |
Yang Li | 35 | 659 | 125.00 |
Jingwen Xu | 36 | 0 | 0.34 |
Haiqiang Wang | 37 | 0 | 0.34 |
Yiting Liao | 38 | 0 | 0.34 |
Junlin Li | 39 | 0 | 0.34 |
Kele Xu | 40 | 46 | 21.80 |
Tao Sun | 41 | 0 | 0.34 |
Yunsheng Xiong | 42 | 0 | 0.34 |
Abhisek Keshari | 43 | 0 | 0.34 |
Komal Komal | 44 | 0 | 0.34 |
Sadbhawana Thakur | 45 | 0 | 0.34 |
Vinit Jakhetiya | 46 | 0 | 0.34 |
Badri N Subudhi | 47 | 0 | 0.34 |
Hao-Hsiang Yang | 48 | 0 | 1.01 |
Hua-En Chang | 49 | 0 | 1.01 |
Zhi-Kai Huang | 50 | 0 | 1.35 |