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NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results

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Main Authors:	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, Hu, Yuhang
Format:	Preprint
Published:	2024
Subjects:	Image and Video Processing Artificial Intelligence
Online Access:	Acceder al recurso
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_version_	1866916210264768512
author	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 Hu, Yuhang
author_facet	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 Hu, Yuhang
contents	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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2404_11313
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results 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 Hu, Yuhang Image and Video Processing Artificial Intelligence 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.
title	NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results
topic	Image and Video Processing Artificial Intelligence
url	https://arxiv.org/abs/2404.11313