MSUE: Multi-Modal Soccer Understanding Expert
This paper presents our solution to the 2026 SoccerNet VQA Challenge. We first develop a cost-effective data synthesis pipeline driven by a Vision-Language Model (VLM), which systematically restructures raw domain data into diverse VQA samples, including concise answers and long-form responses. Second, we propose MSUE, a multi-expert question answering architecture that employs a Large Language Model (LLM) to dynamically dispatch questions to text, image, and video experts. These experts are instantiated as a strong text baseline Gemini3-Flash, a fine-tuned Qwen3-VL, and an external knowledge base, respectively, working collaboratively to enhance VQA performance. MSUE achieves an accuracy...
| Authors | Litao Li, Yibo Yu, Yufeng Hu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 10 June 2026 |
| Last updated at source | 10 June 2026 |
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