Accès ouvert déclaré
2025
preprint
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results
Xin Li, Kun Yuan, Bingchen Li, Fengbin Guan, Yizhen Shao, Zihao Yu, Xijun Wang, Yiting Lu, Wei Hua Luo, Suhang Yao, Ming Sun, Chao Zhou, Zhibo Chen, Radu Timofte, Yabin Zhang, Aoxiang Zhang, Tianwu Zhi, Jianzhao Liu, Yang Li, Jingwen Xu, Yiting Liao, Yushen Zuo, Mingyang Wu, Renjie Li, Zhengzhong Tu, Yufan Liu, Xiangguang Chen, Zuowei Cao, Minhao Tang, Shan Ting Liu, Kexin Zhang, Jingfen Xie, Yan Wang, Kai Chen, Shijie Zhao, Yunchen Zhang, Xiangkai Xu, Hong Xiu Gao, Ji Shi, Yiming Bao, X. Dong, Xiangsheng Zhou, Yaofeng Tu, Ying Liang, Yiwen Wang, Xinning Chai, Yuxuan Zhang, Zhengxue Cheng, Yucai Yang, Rong Xie, Song Li, Wei Sun, Kang Fu, Linhan Cao, Dandan Zhu, Kaiwei Zhang, Yucheng Zhu, Zicheng Zhang, Menghan Hu, Xiongkuo Min, Guangtao Zhai, Zhi Gang Jin, Jiawei Wu, Wei Wang, Wenjian Zhang, Yuhai Lan, Gaoxiong Yi, Huimin Na, Wang Luo, Di Xiao Wu, M. Bai, Juan Du, Zilong Lu, Zhenyu Jiang, Hui Zeng, Ziguan Cui, Zongliang Gan, Guijin Tang, Xing-Lin Xie, Xiaoqiang Lu, Licheng Jiao, Fang Liu, Xu Liu, Puhua Chen, Ha Thu Nguyen, Katrien De Moor, Seyed Ali Amirshahi, Mohamed–Chaker Larabi, Qingjuan Tang, Linfeng He, Zhiyong Gao, Zixuan Gao, Guohua Zhang, Zhi Huang, Yi Deng, Qingmiao Jiang, Lu Chen, Yi Yang, Xi Liao, Nourine Mohammed Nadir, Yuxuan Jiang, Qiang Zhu, Siyue Teng, Fan Zhang, Bing Zeng, Meiqin Liu, Chao Yao, Yao Zhao
0Citations signalées, ce qui n’est pas une note de qualité
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Le résumé fourni par la source
This paper presents a review for the NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement. The challenge comprises two tracks: (i) Efficient Video Quality Assessment (KVQ), and (ii) Diffusion-based Image Super-Resolution (KwaiSR). Track 1 aims to advance the development of lightweight and efficient video quality assessment (VQA) models, with an emphasis on eliminating reliance on model ensembles, redundant weights, and other computationally expensive components in the previous IQA/VQA competitions. Track 2 introduces a new short-form UGC dataset tailored for single image super-resolution, i.e., the KwaiSR dataset. It consists of 1,800 synthetically generated S-UGC image pairs and 1,900 real-world S-UGC images, which are split into training, validation, and test sets using a ratio of 8:1:1. The primary objective of the challenge is to drive research that benefits the user experience of short-form UGC platforms such as Kwai and TikTok. This challenge attracted 266 participants and received 18 valid final submissions with corresponding fact sheets, significantly contributing to the progress of short-form UGC VQA and image superresolution. The project is publicly available at https://github.com/lixinustc/KVQE- ChallengeCVPR-NTIRE2025.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
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Les sujets associés
Image and Video Quality AssessmentAdvanced Image Processing TechniquesVideo Coding and Compression Technologies