EgoEsportsQA: An Egocentric Video Benchmark for Perception and Reasoning in Esports
While video large language models (Video-LLMs) excel in understanding slow-paced, real-world egocentric videos, their capabilities in high-velocity, information-dense virtual environments remain under-explored. Existing benchmarks focus on daily activities, yet lack a rigorous testbed for evaluating fast, rule-bound reasoning in virtual scenarios. To fill this gap, we introduce EgoEsportsQA, a pioneering video question-answering (QA) benchmark for grounding perception and reasoning in expert esports knowledge. We curate 1,745 high-quality QA pairs from professional matches across 3 first-person shooter games via a scalable six-stage pipeline. These questions are structured into a two-dime...
| Authors | Jianzhe Ma, Zhonghao Cao, Shangkui Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 14 April 2026 |
| Last updated at source | 20 April 2026 |
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