High-Speed Vision Improves Zero-Shot Semantic Understanding of Human Actions

ArXi:2605.00496v1 Announce Type: new Understanding human actions from visual observations is essential for human--robot interaction, particularly when semantic interpretation of unfamiliar or hard-to-annotate actions is required. In scenarios such as rapid and less common activities, collecting sufficient labeled data for supervised learning is challenging, making zero-shot approaches a practical alternative for semantic understanding without task-specific