computer-vision-1

Physical Video Anomaly Detection

3260 papers • 126 benchmarks • 313 datasets

Detecting if an entire short clip of a physical or mechanical process features an anomalous motion

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Most implemented papers

Learning Memory-Guided Normality for Anomaly Detection

Bumsub Ham, Hyunjong Park, Jongyoun Noh•Sun Mar 29 2020

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.

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Approaches Toward Physical and General Video Anomaly Detection

Laura Kart, Niv Cohen•Mon Dec 13 2021

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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