VQualA 2025 Challenge on Engagement Prediction for Short Videos: Methods and Results

• URL: http://arxiv.org/abs/2509.02969v1
• Date: Wed, 03 Sep 2025 03:14:23 GMT
• Title: VQualA 2025 Challenge on Engagement Prediction for Short Videos: Methods and Results
• Authors: Dasong Li, Sizhuo Ma, Hang Hua, Wenjie Li, Jian Wang, Chris Wei Zhou, Fengbin Guan, Xin Li, Zihao Yu, Yiting Lu, Ru-Ling Liao, Yan Ye, Zhibo Chen, Wei Sun, Linhan Cao, Yuqin Cao, Weixia Zhang, Wen Wen, Kaiwei Zhang, Zijian Chen, Fangfang Lu, Xiongkuo Min, Guangtao Zhai, Erjia Xiao, Lingfeng Zhang, Zhenjie Su, Hao Cheng, Yu Liu, Renjing Xu, Long Chen, Xiaoshuai Hao, Zhenpeng Zeng, Jianqin Wu, Xuxu Wang, Qian Yu, Bo Hu, Weiwei Wang, Pinxin Liu, Yunlong Tang, Luchuan Song, Jinxi He, Jiaru Wu, Hanjia Lyu,
• Abstract summary: This paper presents an overview of the VQualA 2025 Challenge on Engagement Prediction for Short Videos, held in conjunction with ICCV 2025.<n>The challenge focuses on understanding and modeling the popularity of user-generated content (UGC) short videos on social media platforms.<n>The objective of the Challenge is to promote robust modeling strategies that capture the complex factors influencing user engagement.
• Score: 119.8174531909733
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: This paper presents an overview of the VQualA 2025 Challenge on Engagement Prediction for Short Videos, held in conjunction with ICCV 2025. The challenge focuses on understanding and modeling the popularity of user-generated content (UGC) short videos on social media platforms. To support this goal, the challenge uses a new short-form UGC dataset featuring engagement metrics derived from real-world user interactions. This objective of the Challenge is to promote robust modeling strategies that capture the complex factors influencing user engagement. Participants explored a variety of multi-modal features, including visual content, audio, and metadata provided by creators. The challenge attracted 97 participants and received 15 valid test submissions, contributing significantly to progress in short-form UGC video engagement prediction.

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