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NTIRE 2021 Challenge on Perceptual Image Quality Assessment

Authors :
Gu, Jinjin
Cai, Haoming
Dong, Chao
Ren, Jimmy S.
Qiao, Yu
Gu, Shuhang
Timofte, Radu
Cheon, Manri
Yoon, Sungjun
Kang, Byungyeon
Lee, Junwoo
Zhang, Qing
Guo, Haiyang
Bin, Yi
Hou, Yuqing
Luo, Hengliang
Guo, Jingyu
Wang, Zirui
Wang, Hai
Yang, Wenming
Bai, Qingyan
Shi, Shuwei
Xia, Weihao
Cao, Mingdeng
Wang, Jiahao
Chen, Yifan
Yang, Yujiu
Li, Yang
Zhang, Tao
Feng, Longtao
Liao, Yiting
Li, Junlin
Thong, William
Pereira, Jose Costa
Leonardis, Ales
McDonagh, Steven
Xu, Kele
Yang, Lehan
Cai, Hengxing
Sun, Pengfei
Ayyoubzadeh, Seyed Mehdi
Royat, Ali
Fezza, Sid Ahmed
Hammou, Dounia
Hamidouche, Wassim
Ahn, Sewoong
Yoon, Gwangjin
Tsubota, Koki
Akutsu, Hiroaki
Aizawa, Kiyoharu
Gu, Jinjin
Cai, Haoming
Dong, Chao
Ren, Jimmy S.
Qiao, Yu
Gu, Shuhang
Timofte, Radu
Cheon, Manri
Yoon, Sungjun
Kang, Byungyeon
Lee, Junwoo
Zhang, Qing
Guo, Haiyang
Bin, Yi
Hou, Yuqing
Luo, Hengliang
Guo, Jingyu
Wang, Zirui
Wang, Hai
Yang, Wenming
Bai, Qingyan
Shi, Shuwei
Xia, Weihao
Cao, Mingdeng
Wang, Jiahao
Chen, Yifan
Yang, Yujiu
Li, Yang
Zhang, Tao
Feng, Longtao
Liao, Yiting
Li, Junlin
Thong, William
Pereira, Jose Costa
Leonardis, Ales
McDonagh, Steven
Xu, Kele
Yang, Lehan
Cai, Hengxing
Sun, Pengfei
Ayyoubzadeh, Seyed Mehdi
Royat, Ali
Fezza, Sid Ahmed
Hammou, Dounia
Hamidouche, Wassim
Ahn, Sewoong
Yoon, Gwangjin
Tsubota, Koki
Akutsu, Hiroaki
Aizawa, Kiyoharu
Publication Year :
2021

Abstract

This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2021. As a new type of image processing technology, perceptual image processing algorithms based on Generative Adversarial Networks (GAN) have produced images with more realistic textures. These output images have completely different characteristics from traditional distortions, thus pose a new challenge for IQA methods to evaluate their visual quality. In comparison with previous IQA challenges, the training and testing datasets in this challenge include the outputs of perceptual image processing algorithms and the corresponding subjective scores. Thus they can be used to develop and evaluate IQA methods on GAN-based distortions. The challenge has 270 registered participants in total. In the final testing stage, 13 participating teams submitted their models and fact sheets. Almost all of them have achieved much better results than existing IQA methods, while the winning method can demonstrate state-of-the-art performance.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1269548860
Document Type :
Electronic Resource