Novel Semantic Prompting for Zero-Shot Action Recognition

ArXi:2603.08289v1 Announce Type: new Zero-shot action recognition relies on transferring knowledge from vision-language models to unseen actions using semantic descriptions. While recent methods focus on temporal modeling or architectural adaptations to handle video data, we argue that semantic prompting alone provides a strong and underexplored signal for zero-shot action understanding. We