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NTIRE 2023 Challenge on 360° Omnidirectional Image and Video Super-Resolution: Datasets, Methods and Results
2023
会议录名称IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS
ISSN2160-7508
卷号2023-June
页码1731-1745
发表状态已发表
DOI10.1109/CVPRW59228.2023.00174
摘要

This report introduces two high-quality datasets Flickr360 and ODV360 for omnidirectional image and video super-resolution, respectively, and reports the NTIRE 2023 challenge on 360° omnidirectional image and video super-resolution. Unlike ordinary 2D images/videos with a narrow field of view, omnidirectional images/videos can represent the whole scene from all directions in one shot. There exists a large gap between omnidirectional image/video and ordinary 2D image/video in both the degradation and restoration processes. The challenge is held to facilitate the development of omnidirectional image/video super-resolution by considering their special characteristics. In this challenge, two tracks are provided: one is the omnidirectional image super-resolution and the other is the omnidirectional video super-resolution. The task of the challenge is to super-resolve an input omnidirectional image/video with a magnification factor of ×4. Realistic omnidirectional downsampling is applied to construct the datasets. Some general degradation(e.g., video compression) is also considered for the video track. The challenge has 100 and 56 registered participants for those two tracks. In the final testing stage, 7 and 3 participating teams submitted their results, source codes, and fact sheets. Almost all teams achieved better performance than baseline models by integrating omnidirectional characteristics, reaching compelling performance on our newly collected Flickr360 and ODV360 datasets. © 2023 IEEE.

关键词Computer vision Optical resolving power 2D images Degradation process Field of views High quality Image super resolutions Magnification factors Omnidirectional image Performance Restoration process Video super-resolution
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20233714730753
EI主题词Image compression
EISSN2160-7516
EI分类号723.5 Computer Applications ; 741.1 Light/Optics ; 741.2 Vision
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/348760
专题信息科学与技术学院_硕士生
信息科学与技术学院
通讯作者Cao, Mingdeng
作者单位
1.The University of Tokyo, Japan
2.Arc Lab, Tencent Pcg, China
3.Peking University, China
4.Shenzhen Institute of Advanced Technology, Cas, China
5.Platform Technologies, Tencent Online Video, China
6.Computer Vision Lab, Ifi & Caidas, University of Würzburg, Germany
7.ByteDance, China
8.Peking University, Shenzhen Graduate School, China
9.Mais&cripac, Institute of Automation, Chinese Academy of Sciences, China
10.School of Artificial Intelligence, University of Chinese Academy of Sciences, China
11.University of Science and Technology of China, China
12.Beijing Institute of Technology, China
13.School of Information Science and Technology, ShanghaiTech University, China
14.Harbin Institute of Technology, China
15.Graduate Institute of Electronics Engineering, National Taiwan University, Taiwan
16.Department of Electrical Engineering, National Taiwan University, Taiwan
17.Graduate Institute of Communication Engineering, National Taiwan University, Taiwan
18.ServiceNow, United States
19.ShanghaiTech University, China
20.Meituan, China
21.Xiaomi Inc
推荐引用方式
GB/T 7714
Cao, Mingdeng,Mou, Chong,Yu, Fanghua,et al. NTIRE 2023 Challenge on 360° Omnidirectional Image and Video Super-Resolution: Datasets, Methods and Results[C]:IEEE Computer Society,2023:1731-1745.
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