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CutPaste: Self-Supervised Learning for Anomaly Detection and Localization

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), (2021)

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Abstract

We aim at constructing a high performance model for defect detection that detects unknown anomalous patterns of an image without anomalous data. To this end, we propose a two-stage framework for building anomaly detectors using normal training data only. We first learn self-supervised deep representations and then build a generative one...More

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Author
Chun-Liang Li
Chun-Liang Li
Kihyuk Sohn
Kihyuk Sohn
Jinsung Yoon
Jinsung Yoon
Tomas Pfister
Tomas Pfister
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