Sept. 26, 2022, 1:14 a.m. | Khalil Bergaoui, Yassine Naji, Aleksandr Setkov, Angélique Loesch, Michèle Gouiffès, Romaric Audigier

cs.CV updates on arXiv.org arxiv.org

This paper addresses video anomaly detection problem for videosurveillance.
Due to the inherent rarity and heterogeneity of abnormal events, the problem is
viewed as a normality modeling strategy, in which our model learns
object-centric normal patterns without seeing anomalous samples during
training. The main contributions consist in coupling pretrained object-level
action features prototypes with a cosine distance-based anomaly estimation
function, therefore extending previous methods by introducing additional
constraints to the mainstream reconstruction-based strategy. Our framework
leverages both appearance and motion …

anomaly anomaly detection arxiv detection memory normality video

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