SoccerMaster: A Vision Foundation Model for Soccer Understanding

• URL: http://arxiv.org/abs/2512.11016v1
• Date: Thu, 11 Dec 2025 18:03:30 GMT
• Title: SoccerMaster: A Vision Foundation Model for Soccer Understanding
• Authors: Haolin Yang, Jiayuan Rao, Haoning Wu, Weidi Xie,
• Abstract summary: Soccer understanding has recently garnered growing research interest due to its domain-specific complexity and unique challenges.<n>This work aims to propose a unified model to handle diverse soccer visual understanding tasks, ranging from fine-grained perception to semantic reasoning.<n>We present SoccerMaster, the first soccer-specific vision foundation model that unifies diverse understanding tasks within a single framework.
• Score: 50.88251190999469
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Soccer understanding has recently garnered growing research interest due to its domain-specific complexity and unique challenges. Unlike prior works that typically rely on isolated, task-specific expert models, this work aims to propose a unified model to handle diverse soccer visual understanding tasks, ranging from fine-grained perception (e.g., athlete detection) to semantic reasoning (e.g., event classification). Specifically, our contributions are threefold: (i) we present SoccerMaster, the first soccer-specific vision foundation model that unifies diverse understanding tasks within a single framework via supervised multi-task pretraining; (ii) we develop an automated data curation pipeline to generate scalable spatial annotations, and integrate them with various existing soccer video datasets to construct SoccerFactory, a comprehensive pretraining data resource; and (iii) we conduct extensive evaluations demonstrating that SoccerMaster consistently outperforms task-specific expert models across diverse downstream tasks, highlighting its breadth and superiority. The data, code, and model will be publicly available.

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