MSAF: Multimodal Supervise-Attention Enhanced Fusion for Video Anomaly Detection
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DOI: 10.1109/lsp.2022.3216500
Abstract: The complementarity of multimodal signal is essential for video anomaly detection. However, existing methods either lack exploration to multimodal data or ignore the implicit alignment of multimodal features. In our work, we address this problem… read more here.
Keywords: video anomaly; multimodal supervise; fusion; supervise attention ... See more keywords