Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection
Weakly supervised anomaly detection is a challenging task since frame-level labels are not given in the training phase. Previous studies generally employ neural networks to learn features and produce frame-level predictions and then use multiple instance learning (MIL)-based classification loss to e...
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 30(2021) vom: 01., Seite 3513-3527 |
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| Format: | Article en ligne |
| Langue: | English |
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2021
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Sujets: | Journal Article |
| Accès en ligne |
Volltext |