AINeutralarXiv – CS AI · 18h ago6/10
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MemoVAD: Resource-Efficient Video Anomaly Detection via Dynamic Semantic Memory in Edge Computing Scenarios
Researchers introduce MemoVAD, an edge-cloud collaborative framework that enables efficient video anomaly detection on resource-constrained devices by selectively querying cloud-based Vision-Language Models only for uncertain or novel scenarios. The system uses dynamic semantic memory to cache verified patterns, reducing computational overhead while maintaining detection accuracy on surveillance tasks.