Sparsity-Controllable Normality Learning With Vision–Language Models for Scenario-Related Video Anomaly Detection
Video anomaly detection (VAD) is critical for automation systems and security surveillance. Recently, multimodal vision–language models (MLLMs) have attracted increasing attention due to their rich pre-trained knowledge and strong explainability. However, existing MLLM-based approaches struggle to adapt to real-world s...