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  1. Paul BERGMANN | Cited by 2,536 | of Technische Universität München, München (TUM) | Read 15 publications | Contact Paul BERGMANN

  2. 6 nov 2019 · Paul Bergmann, Michael Fauser, David Sattlegger, Carsten Steger. We introduce a powerful student-teacher framework for the challenging problem of unsupervised anomaly detection and pixel-precise anomaly segmentation in high-resolution images.

    • Paul Bergmann, Michael Fauser, David Sattlegger, Carsten Steger
    • arXiv:1911.02357 [cs.CV]
    • 2019
    • Accepted to CVPR 2020
  3. 5 lug 2018 · Paul Bergmann, Sindy Löwe, Michael Fauser, David Sattlegger, Carsten Steger. 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 reconstruction error based on an ℓp distance.

    • Paul Bergmann, Sindy Löwe, Michael Fauser, David Sattlegger, Carsten Steger
    • 2018
  4. Daniel Cremers Technical University of MunichVerified email at tum.de. Lars Heckler PhD Student, MVTec Software GmbH & Technical University of Munich (TUM)Verified email at mvtec.com. Follow. Paul Bergmann. Deep Learning Engineer at Apple. Verified email at apple.com. Computer Vision Anomaly Detection Deep Learning. Title.

  5. Paul Bergmann, Kilian Batzner, Michael Fauser, David Sattlegger, Carsten Steger: Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization; in: International Journal of Computer Vision 130(4):947-969, 2022.

  6. Semantic Scholar profile for Paul Bergmann, with 511 highly influential citations and 21 scientific research papers.

  7. Paul Bergmann, Michael Fauser, David Sattlegger, Carsten Steger; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 9592-9600. Abstract. The detection of anomalous structures in natural image data is of utmost importance for numerous tasks in the field of computer vision.

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