Real-Time Anomaly Detection on Edge Devices via VLM Prompt Optimization
Real-time video anomaly detection (VAD) under realistic edge constraints—sub-second latency, ≤25 W power, no cloud dependency, and human-interpretable output—remains an open problem. Existing lightweight video convolutional neural networks (X3D, MoViNets) are bound to closed-set training distributions, while recent vis...