RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection

Self-supervised feature reconstruction methods have shown promising advances in industrial image anomaly de-tection and localization. Despite this progress, these meth-ods still face challenges in synthesizing realistic and di-verse anomaly samples, as well as addressing the feature redundancy and p...

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Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 16699 - 16708
Hlavní autori:	Zhang, Ximiao, Xu, Min, Zhou, Xiuzhuang
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 16.06.2024
Predmet:	anomaly detection anomaly synthesis Computer vision Data models Feature extraction feature selection Location awareness Pattern recognition Reconstruction algorithms Redundancy
ISSN:	1063-6919
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