Mohamed Mahmoud

SETAS-VAD: Semantically Enriched Text-Aligned Scoring for Weakly Supervised Video Anomaly Detection

Weakly supervised video anomaly detection (WS-VAD) localizes anomalous events in untrimmed videos using only video-level annotations. While CLIP-based methods have advanced this task through vision–language alignment, widely adopted approaches construct text prototypes from short...