Authors
Mingdeng Cao, Chong Mou, Fanghua Yu, Xintao Wang, Yinqiang Zheng, Jian Zhang, Chao Dong, Gen Li, Ying Shan, Radu Timofte, Xiaopeng Sun, Weiqi Li, Zhenyu Zhang, Xuhan Sheng, Bin Chen, Haoyu Ma, Ming Cheng, Shijie Zhao, Wanwan Cui, Tianyu Xu, Chunyang Li, Long Bao, Heng Sun, Huaibo Huang, Xiaoqiang Zhou, Yuang Ai, Ran He, Renlong Wu, Yi Yang, Zhilu Zhang, Shuohao Zhang, Junyi Li, Yunjin Chen, Dongwei Ren, Wangmeng Zuo, Qian Wang, Hao-Hsiang Yang, Yi-Chung Chen, Zhi-Kai Huang, Wei-Ting Chen, Yuan-Chun Chiang, Hua-En Chang, I Chen, Chia-Hsuan Hsieh, Sy-Yen Kuo, Zebin Zhang, Jiaqi Zhang, Yuhui Wang, Shuhao Cui, Junshi Huang, Li Zhu, Shuman Tian, Wei Yu, Bingchun Luo
Publication date
2023
Conference
Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
Pages
1731-1745
Description
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 360deg 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 x4. Realistic omnidirectional downsampling is applied to construct the datasets. Some general degradation (eg, 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.
Total citations
Scholar articles
M Cao, C Mou, F Yu, X Wang, Y Zheng, J Zhang… - Proceedings of the IEEE/CVF conference on computer …, 2023