3 papers
cs.AI2026
Glance, Scrutinize, and Think: Advancing Video Anomaly Detection from Training-Free to Agentic Reasoning
Shibo Gao, Peipei Yang, Xu-Yao Zhang +1
Video Anomaly Detection (VAD) aims to identify anomalous events and localize their temporal intervals. Existing approaches exhibit a "when-what" dissociation: traditional DNN-based…
cs.CV2025
The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM
Shibo Gao, Peipei Yang, Haiyang Guo +7
Video anomaly detection (VAD) aims to identify and ground anomalous behaviors or events in videos, serving as a core technology in the fields of intelligent surveillance and public…
cs.CV2025
VAGU & GtS: LLM-Based Benchmark and Framework for Joint Video Anomaly Grounding and Understanding
Shibo Gao, Peipei Yang, Yangyang Liu +4
Video Anomaly Detection (VAD) aims to identify anomalous events in videos and accurately determine their time intervals. Current VAD methods mainly fall into two categories: tradit…