Strictly Causal Streaming Video Anomaly Detection with a Theoretically-Grounded State-Space Core

AI Digest - ArXiv AI

Strictly Causal Streaming Video Anomaly Detection with a Theoretically-Grounded State-Space Core

Recent work has applied Mamba style state space models (SSMs) to video anomaly detection, yet existing approaches still rely on buffering clips or windows internally, lack a theoretical account of how temporal memory relates to detection latency, and benchmark efficiency only through GPU throughput rather than the edge hardware these methods are intended to target. We introduce a strictly causal streaming anomaly detector whose fixed size state is updated in O(1) time and memory per incoming fra

Source: ArXiv AI