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4 results on '"Haoming Cai"'

2. NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

Author

Yawei Li, Kai Zhang, Radu Timofte, Luc Van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wul, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoglu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gao, Dengwen Zhou, Qian Ning, Jingzhu Tang, Han Huang, Yufei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Kun Zeng, Hanjiang Lin, Xinyu Chen, and Jinsheng Fang

Published
2022
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4. NTIRE 2021 Challenge on Perceptual Image Quality Assessment

Author

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

Subjects
FOS: Computer and information sciences, business.industry, Computer science, Image quality, Computer Vision and Pattern Recognition (cs.CV), media_common.quotation_subject, Distortion (optics), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Image processing, Electrical Engineering and Systems Science - Image and Video Processing, Visualization, FOS: Electrical engineering, electronic engineering, information engineering, Quality (business), Perceptual image quality, Computer vision, Artificial intelligence, business, Perceptual image, Image restoration, media_common
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.

Published
2021
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