MSUE: Multi-Modal Soccer Understanding Expert Achieves Third Place in SoccerNet VQA Challenge
Researchers have proposed MSUE, a multi-modal AI architecture for soccer video understanding that scored 0.95 accuracy on the 2026 SoccerNet VQA Challenge benchmark, placing third. The system combines a data synthesis pipeline with a multi-expert routing framework that dispatches questions to specialized text, image, and video processing modules. The work demonstrates how combining large language models with domain-specific fine-tuning and external knowledge bases can yield high performance on sports video question answering tasks.
MSUE (Multi-Modal Soccer Understanding Expert) is a system developed as a submission to the 2026 SoccerNet Visual Question Answering (VQA) Challenge. The approach consists of two main components: a cost-effective data synthesis pipeline that uses a Vision-Language Model to convert raw soccer domain data into diverse VQA training samples, including both concise and long-form answers; and a multi-expert question answering architecture that uses a Large Language Model as a dynamic dispatcher. The dispatcher routes incoming questions to one of three specialized experts: a text baseline powered by Gemini3-Flash, a fine-tuned Qwen3-VL model for image understanding, and an external soccer knowledge base. These experts work collaboratively to address the multimodal nature of soccer video queries. The system achieved an accuracy of 0.95 on the challenge benchmark, securing third place on the leaderboard, and is described in a 6-page paper submitted to arXiv in June 2026.
What's missing
The paper does not detail the composition or size of the test set used for the 0.95 accuracy figure, nor does it report performance breakdowns across question types (e.g., text-only vs. video-grounded queries). The gap between MSUE and the first- and second-place systems is not disclosed, limiting assessment of how competitive third place actually was. Generalizability beyond soccer-domain VQA is not evaluated.
What different sources said
- arXiv cs.AICenter
MSUE: Multi-Modal Soccer Understanding Expert
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