2 papers
cs.CV2019
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…
cs.CV2018
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…