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ReactVAU introduces a slow-fast decoupled framework for real-time streaming video anomaly understanding, leveraging a fast detection module, persistent anomaly-aware memory, and on-demand slow reasoning to enhance efficiency and performance.
This paper presents a unified global-to-local paradigm for video anomaly detection, introducing a training-free framework (GtS) and a tool-augmented agentic reasoning method with reinforcement learning, along with a new benchmark VAGU-T and metric JeAUG.