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PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

ICPR Workshops, 2020
We present a new framework for Patch Distribution Modeling, PaDiM, to concurrently detect and localize anomalies in images in a one-class learning setting.
Thomas Defard   +3 more
semanticscholar   +1 more source

Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation

Asian Conference on Computer Vision, 2020
In this paper, we address the problem of image anomaly detection and segmentation. Anomaly detection involves making a binary decision as to whether an input image contains an anomaly, and anomaly segmentation aims to locate the anomaly on the pixel ...
Jihun Yi, Sungroh Yoon
semanticscholar   +1 more source

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