arXiv AI July 13, 2026 By Peipei Zhu, Yueqing Niu, Lin Zhu, Guanchong Niu, Yang Yu, Zheng Li

Event Stream based Multi-Modal Video Anomaly Detection: A Benchmark Dataset and Algorithms

arXiv:2607. 09114v1 Announce Type: cross Abstract: Video anomaly detection (VAD) is critical for automated surveillance but remains fragile under challenging conditions such as illumination variations, fast motion, and complex backgrounds when relying solely on visible light videos.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

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