916 citations · 1.6k across the 5 of their papers we have counts for
5 papers
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…
The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization
Paul Bergmann, Xin Jin, David Sattlegger +1
We introduce the first comprehensive 3D dataset for the task of unsupervised anomaly detection and localization. It is inspired by real-world visual inspection scenarios in which a…
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…
Online Photometric Calibration for Auto Exposure Video for Realtime Visual Odometry and SLAM
Paul Bergmann, Rui Wang, Daniel Cremers
Recent direct visual odometry and SLAM algorithms have demonstrated impressive levels of precision. However, they require a photometric camera calibration in order to achieve compe…