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Object-centric and memory-guided normality reconstruction for video anomaly detection. (arXiv:2203.03677v3 [cs.CV] UPDATED)
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