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Find defects in part images when only train with defect-free images

Find defects in part images when only train with defect-free images


Towards Total Recall in Industrial Anomaly Detection



Being able to spot defective parts is a critical component in large-scale industrial manufacturing.


... challenge that we address ... fit a model using nominal (non-defective) example images only.


... goal is to build systems that work well simultaneously on many different tasks automatically.


... propose PatchCore, which uses a maximally representative memory bank of nominal patch-features.


... competitive inference times while achieving state-of-the-art performance for both detection and localization.


On the standard dataset MVTec AD, PatchCore achieves an image-level anomaly detection AUROC score of 99.1%, more than halving the error compared to the next best competitor. ...



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