5 citations · 5 across the 1 of their papers we have counts for
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Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors
Paul Bergmann, David Sattlegger
We present a new method for the unsupervised detection of geometric anomalies in high-resolution 3D point clouds. In particular, we propose an adaptation of the established student…
Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings
Paul Bergmann, Michael Fauser, David Sattlegger +1
We introduce a powerful student-teacher framework for the challenging problem of unsupervised anomaly detection and pixel-precise anomaly segmentation in high-resolution images. St…
Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders
Paul Bergmann, Sindy Löwe, Michael Fauser +2
Convolutional autoencoders have emerged as popular methods for unsupervised defect segmentation on image data. Most commonly, this task is performed by thresholding a pixel-wise re…