Temporal Action Localization

Temporal action localization (TAL) aims to identify the start and end times of actions within untrimmed videos, a crucial task in video understanding. Current research focuses on improving accuracy and efficiency, particularly in weakly or semi-supervised settings, using architectures like transformers and incorporating multimodal information (audio-visual, text) to enhance performance. These advancements are driving progress in applications such as anomaly detection, driver behavior monitoring, and autism screening, highlighting TAL's growing importance across diverse fields.