Introducing MVTec ITODD - A Dataset for 3D Object Recognition in Industry. - Bertram Drost; Markus Ulrich; Paul Bergmann; Philipp Härtinger; Carsten Steger (ICCV Workshops, 2017)

Online Photometric Calibration of Auto Exposure Video for Realtime Visual Odometry and SLAM. - Paul Bergmann; Rui Wang 037; Daniel Cremers (IEEE Robotics Autom. Lett., 2018)

MVTec AD - A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection. - Paul Bergmann; Michael Fauser; David Sattlegger; Carsten Steger (CVPR, 2019)

Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders. - Paul Bergmann; Sindy Löwe; Michael Fauser; David Sattlegger; Carsten Steger (VISIGRAPP (5: VISAPP), 2019)

Uninformed Students: Student-Teacher Anomaly Detection With Discriminative Latent Embeddings. - Paul Bergmann; Michael Fauser; David Sattlegger; Carsten Steger (CVPR, 2020)

The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection. - Paul Bergmann; Kilian Batzner; Michael Fauser; David Sattlegger; Carsten Steger (Int. J. Comput. Vis., 2021)

The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization. - Paul Bergmann; Xin Jin; David Sattlegger; Carsten Steger (VISIGRAPP (5: VISAPP), 2022)

Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization. - Paul Bergmann; Kilian Batzner; Michael Fauser; David Sattlegger; Carsten Steger (Int. J. Comput. Vis., 2022)

Unsupervised Anomaly Detection and Localization for Visual Quality Inspection. - Paul Bergmann (2022)

Exploring the Importance of Pretrained Feature Extractors for Unsupervised Anomaly Detection and Localization. - Lars Heckler; Rebecca König; Paul Bergmann (CVPR Workshops, 2023)

Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors. - Paul Bergmann; David Sattlegger (WACV, 2023)