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Latha Pemula

2 accepted papers

2022

SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation

ECCV 2022poster

"Visual anomaly detection is commonly used in industrial quality inspection. In this paper, we present a new dataset as well as a new self-supervised learning method for ImageNet pre-training to improve anomaly detection and segmentation in 1-class and 2-class 5/10/high-shot training setups. We rele…

2022

Towards Total Recall in Industrial Anomaly Detection

CVPR 2022poster

Being able to spot defective parts is a critical component in large-scale industrial manufacturing. A particular challenge that we address in this work is the cold-start problem: fit a model using nominal (non-defective) example images only. While handcrafted solutions per class are possible, the go…

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