Multimodal and multiscale feature fusion for weakly supervised video anomaly detection
Abstract Weakly supervised video anomaly detection aims to detect anomalous events with only video-level labels. In the absence of boundary information for anomaly segments, most existing methods rely on multiple instance learning. In these approaches, the predictions for unlabeled video snippets ar...
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| Hlavní autoři: | , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
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Nature Portfolio
2024-10-01
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| Edice: | Scientific Reports |
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| On-line přístup: | https://doi.org/10.1038/s41598-024-73462-0 |
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