1. NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results
- Author
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Li, Xin, Yuan, Kun, Pei, Yajing, Lu, Yiting, Sun, Ming, Zhou, Chao, Chen, Zhibo, Timofte, Radu, Sun, Wei, Wu, Haoning, Zhang, Zicheng, Jia, Jun, Zhang, Zhichao, Cao, Linhan, Chen, Qiubo, Min, Xiongkuo, Lin, Weisi, Zhai, Guangtao, Sun, Jianhui, Wang, Tianyi, Li, Lei, Kong, Han, Wang, Wenxuan, Li, Bing, Luo, Cheng, Wang, Haiqiang, Chen, Xiangguang, Meng, Wenhui, Pan, Xiang, Shi, Huiying, Zhu, Han, Xu, Xiaozhong, Sun, Lei, Chen, Zhenzhong, Liu, Shan, Kong, Fangyuan, Fan, Haotian, Xu, Yifang, Xu, Haoran, Yang, Mengduo, Zhou, Jie, Li, Jiaze, Wen, Shijie, Xu, Mai, Li, Da, Yao, Shunyu, Du, Jiazhi, Zuo, Wangmeng, Li, Zhibo, He, Shuai, Ming, Anlong, Fu, Huiyuan, Ma, Huadong, Wu, Yong, Xue, Fie, Zhao, Guozhi, Du, Lina, Guo, Jie, Zhang, Yu, Zheng, Huimin, Chen, Junhao, Liu, Yue, Zhou, Dulan, Xu, Kele, Xu, Qisheng, Sun, Tao, Ding, Zhixiang, and Hu, Yuhang
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Artificial Intelligence - Abstract
This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected dataset KVQ from popular short-form video platform, i.e., Kuaishou/Kwai Platform. The KVQ database is divided into three parts, including 2926 videos for training, 420 videos for validation, and 854 videos for testing. The purpose is to build new benchmarks and advance the development of S-UGC VQA. The competition had 200 participants and 13 teams submitted valid solutions for the final testing phase. The proposed solutions achieved state-of-the-art performances for S-UGC VQA. The project can be found at https://github.com/lixinustc/KVQChallenge-CVPR-NTIRE2024., Comment: Accepted by CVPR2024 Workshop. The challenge report for CVPR NTIRE2024 Short-form UGC Video Quality Assessment Challenge
- Published
- 2024