3260 papers • 126 benchmarks • 313 datasets
Detecting if an entire short clip of a any action features an anomalous motion - another action class not seen during training.
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This work proposes to use a memory module with a new update scheme where items in the memory record prototypical patterns of normal data, boosting the discriminative power of both memory items and deeply learned features from normal data and lessening the representation capacity of CNNs.
This work introduces the Physical Anomalous Trajectory or Motion (PHANTOM) dataset 1, which contains six different video classes, which differs in the presented phenomena, the normal class variability, and the kind of anomalies in the videos.
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