ShanghaiTech University Knowledge Management System
| NTIRE 2023 Challenge on Image Super-Resolution (×4): Methods and Results | |
Zhang, Yulun1; Zhang, Kai1; Chen, Zheng2; Li, Yawei1; Timofte, Radu3; Zhang, Junpei4; Zhang, Kexin4; Peng, Rui4; Ma, Yanbiao4; Jiao, Licheng4; Huang, Huaibo5,6; Zhou, Xiaoqiang5,7; Ai, Yuang5,8; He, Ran5,6,9  ; Qiu, Yajun10; Zhu, Qiang10; Li, Pengfei10; Li, Qianhui10; Zhu, Shuyuan10; Zhang, Dafeng11; Li, Jia11; Wang, Fan11; Li, Chunmiao11; Kim, TaeHyung12; Kil, Jungkeong12; Kim, Eon12; Yu, Yeonseung12; Lee, Beomyeol12; Lee, Subin12; Lim, Seokjae12; Chae, Somi12; Choi, Heungjun12; Huang, ZhiKai14; Chen, YiChung15; Chiang, YuanChun14; Yang, HaoHsiang14; Chen, WeiTing13; Chang, HuaEn14; Chen, I-Hsiang14; Hsieh, ChiaHsuan16; Kuo, SyYen14; Choi, Ui-Jin17; Conde, Marcos V.18; Khowaja, Sunder Ali19; Yoon, Jiseok20; Lee, Ik Hyun20; Gendy, Garas21; Sabor, Nabil22; Hou, Jingchao21; He, Guanghui21; Zhang, Zhao23; Li, Baiang23; Zheng, Huan23; Zhao, Suiyi23; Gao, Yangcheng23; Wei, Yanyan23; Ren, Jiahuan23; Wei, Jiayu24; Li, Yanfeng24; Sun, Jia24; Cheng, Zhanyi24; Li, Zhiyuan24; Yao, Xu24; Wang, Xinyi27; Li, Danxu27; Cui, Xuan27; Cao, Jun27; Li, Cheng27; Zheng, Jianbin25; Sarvaiya, Anjali26; Prajapati, Kalpesh26; Patra, Ratnadeep26; Barik, Pragnesh26; Rathod, Chaitanya26; Upla, Kishor26; Raja, Kiran27; Ramachandra, Raghavendra27; Busch, Christoph27
| |
| 2023 | |
| 会议录名称 | IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS |
| ISSN | 2160-7508 |
| 卷号 | 2023-June |
| 页码 | 1865-1884 |
| 发表状态 | 已发表 |
| DOI | 10.1109/CVPRW59228.2023.00185 |
| 摘要 | This paper reviews the NTIRE 2023 challenge on image super-resolution (×4), focusing on the proposed solutions and results. The task of image super-resolution (SR) is to generate a high-resolution (HR) output from a corresponding low-resolution (LR) input by leveraging prior information from paired LR-HR images. The aim of the challenge is to obtain a network design/solution capable to produce high-quality results with the best performance (e.g., PSNR). We want to explore how high performance we can achieve regardless of computational cost (e.g., model size and FLOPs) and data. The track of the challenge was to measure the restored HR images with the ground truth HR images on DIV2K testing dataset. The ranking of the teams is determined directly by the PSNR value. The challenge has attracted 192 registered participants, where 15 teams made valid submissions. They achieve state-of-the-art performance in single image super-resolution. © 2023 IEEE. |
| 关键词 | Computer vision Optical resolving power Computational costs Design solutions High quality High-resolution images High-resolution output Image super resolutions Lower resolution Network design Performance Prior information |
| 会议名称 | 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 |
| 会议地点 | Vancouver, BC, Canada |
| 会议日期 | June 18, 2023 - June 22, 2023 |
| 收录类别 | EI |
| 语种 | 英语 |
| 出版者 | IEEE Computer Society |
| EI入藏号 | 20233714731027 |
| EI主题词 | Statistical tests |
| EISSN | 2160-7516 |
| EI分类号 | 723.5 Computer Applications ; 741.1 Light/Optics ; 741.2 Vision ; 922.2 Mathematical Statistics |
| 原始文献类型 | Conference article (CA) |
| 文献类型 | 会议论文 |
| 条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/348761 |
| 专题 | 信息科学与技术学院 |
| 通讯作者 | Zhang, Kai |
| 作者单位 | 1.Computer Vision Lab, Eth Zurich, Switzerland 2.Shanghai Jiao Tong University, China 3.University of Würzburg, Germany 4.Xidian University, China 5.Mais&cripac, Institute of Automation, Chinese Academy of Sciences, China 6.School of Artificial Intelligence, University of Chinese Academy of Sciences, China 7.University of Science and Technology of China, China 8.Beijing Institute of Technology, China 9.School of Information Science and Technology, ShanghaiTech University, China 10.School of Information and Communication Engineering, University of Electronic Science and Technology of China, China 11.Samsung Research China - Beijing (SRC-B), China 12.Lotte Data Communication Company, Seoul, Korea, Republic of 13.Graduate Institute of Electronics Engineering, National Taiwan University, Taiwan 14.Department of Electrical Engineering, National Taiwan University, Taiwan 15.Graduate Institute of Communication Engineering, National Taiwan University, Taiwan 16.ServiceNow, United States 17.MegaStudyEdu, Korea, Republic of 18.Computer Vision Lab, Caidas, University of Würzburg, Germany 19.University of Sindh, Pakistan 20.Iklab Inc., Tech University of Korea, Siheung-Si, Korea, Republic of 21.Micro-Nano Electronics Department, Shanghai Jiao Tong University, China 22.Electrical Engineering Department, Faculty of Engineering, Assiut University, Egypt 23.Hefei University of Technology, China 24.Beijing Jiaotong University, China 25.South China University of Technology, Guangdong, Guangzhou, China 26.Sardar Vallabhbhai National Institute of Technology, India 27.Norwegian University of Science and Technology, Norway |
| 推荐引用方式 GB/T 7714 | Zhang, Yulun,Zhang, Kai,Chen, Zheng,et al. NTIRE 2023 Challenge on Image Super-Resolution (×4): Methods and Results[C]:IEEE Computer Society,2023:1865-1884. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
修改评论
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。