Ask or search anything...

This paper presents a comprehensive survey of Video Anomaly Detection (VAD) research over the past decade, with a particular focus on deep learning methodologies and the burgeoning role of Vision Language Models (VLMs). The survey identifies key challenges in datasets and learning paradigms, demonstrating how VLMs are enhancing anomaly detection performance through richer semantic understanding.