Event Stream based Multi-Modal Video Anomaly Detection: A Benchmark Dataset and Algorithms
英文标题：Event Stream based Multi-Modal Video Anomaly Detection: A Benchmark Dataset and Algorithms
arXiv:2607.09114v1 Announce Type: new 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. To address these l
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中文
arXiv:2607.09114v1 Announce Type: new 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. To address these l
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English / 原文
arXiv:2607.09114v1 Announce Type: new 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. To address these l