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Paul Bergmann
Paul Bergmann
Ph.D. Student at Technical University of Munich and MVTec Software GmbH
Verified email at mvtec.com
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Year
MVTec AD--A comprehensive real-world dataset for unsupervised anomaly detection
P Bergmann, M Fauser, D Sattlegger, C Steger
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
5042019
Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders
P Bergmann, S Löwe, M Fauser, D Sattlegger, C Steger
Proceedings of the 14th International Joint Conference on Computer Vision …, 2019
3252019
Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings
P Bergmann, M Fauser, D Sattlegger, C Steger
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
2322020
The MVTec anomaly detection dataset: a comprehensive real-world dataset for unsupervised anomaly detection
P Bergmann, K Batzner, M Fauser, D Sattlegger, C Steger
International Journal of Computer Vision 129 (4), 1038-1059, 2021
882021
Introducing mvtec itodd-a dataset for 3d object recognition in industry
B Drost, M Ulrich, P Bergmann, P Hartinger, C Steger
Proceedings of the IEEE international conference on computer vision …, 2017
802017
Online photometric calibration of auto exposure video for realtime visual odometry and slam
P Bergmann, R Wang, D Cremers
IEEE Robotics and Automation Letters 3 (2), 627-634, 2017
752017
The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization
P Bergmann, X Jin, D Sattlegger, C Steger
https://arxiv.org/abs/2112.09045, 2021
172021
Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization
P Bergmann, K Batzner, M Fauser, D Sattlegger, C Steger
International Journal of Computer Vision 130 (4), 947-969, 2022
52022
Anomaly detection in 3d point clouds using deep geometric descriptors
P Bergmann, D Sattlegger
arXiv preprint arXiv:2202.11660, 2022
22022
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