Sports-QA is a benchmark dataset proposed in the paper "Sports-QA: A Large-Scale Video Question Answering Benchmark for Complex and Professional Sports". The dataset contains videos and is hosted on HuggingFace by author HopLeeTop, with a last recorded update in December 2025. Further details are referenced to be available on a GitHub page.
Use Cases
- Train video question answering models based on sports video content.
- Benchmark multimodal AI performance on complex, professional sports scenarios.
- Develop systems for automated sports commentary or analysis based on video and textual queries.
Strengths
- Dataset is described as a 'Large-Scale' benchmark in the source paper title.
- Focuses on 'Complex and Professional Sports', suggesting domain-specific complexity.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count, file formats, and license information are unknown, which may limit suitability assessment.
Provenance
- Source
- HuggingFace, author HopLeeTop.
- Collection Method
- Proposed in an academic paper; specific collection method is not detailed in the provided metadata.
- Time Range
- null
- Freshness
- Last updated 2025-12-09 08:11:36; freshness should be verified.
- Geography
- null