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

Published: September 3, 2025 | arXiv ID: 2509.02969v1

By: Dasong Li , Sizhuo Ma , Hang Hua and more

Potential Business Impact:

Predicts which short videos people will like.

Business Areas:
Image Recognition Data and Analytics, Software

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.

Country of Origin
πŸ‡ΊπŸ‡Έ πŸ‡¬πŸ‡§ United States, United Kingdom

Page Count
12 pages

Category
Computer Science:
CV and Pattern Recognition