Daniel Cremers

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Daniel Cremers

Prof. Dr.

1999 …2025

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  • 2020

    Lifting methods for manifold-valued variational problems

    Vogt, T., Strekalovskiy, E., Cremers, D. & Lellmann, J., 3 Apr 2020, Handbook of Variational Methods for Nonlinear Geometric Data. Springer International Publishing, p. 95-119 25 p.

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    5 Scopus citations

  • On the well-posedness of uncalibrated photometric stereo under general lighting

    Brahimi, M., Quéau, Y., Haefner, B. & Cremers, D., 2020, Advances in Computer Vision and Pattern Recognition. Springer Science and Business Media Deutschland GmbH, p. 147-176 30 p. (Advances in Computer Vision and Pattern Recognition).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    Open Access
    7 Scopus citations

  • q-Space Novelty Detection with Variational Autoencoders

    Vasilev, A., Golkov, V., Meissner, M., Lipp, I., Sgarlata, E., Tomassini, V., Jones, D. K. & Cremers, D., 2020, Mathematics and Visualization. Springer Science and Business Media Deutschland GmbH, p. 113-124 12 p. (Mathematics and Visualization).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    Open Access
    26 Scopus citations

  • TUM Flyers: Vision—Based MAV Navigation for Systematic Inspection of Structures

    Usenko, V., von Stumberg, L., Stückler, J. & Cremers, D., 2020, Springer Tracts in Advanced Robotics. Springer, p. 189-209 21 p. (Springer Tracts in Advanced Robotics; vol. 136).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    3 Scopus citations
  • 2019

    A review and quantitative evaluation of direct visual-inertial odometry

    Von Stumberg, L., Usenko, V. & Cremers, D., 1 Jan 2019, Multimodal Scene Understanding: Algorithms, Applications and Deep Learning. Elsevier, p. 159-198 40 p.

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    5 Scopus citations
  • 2018

    Image denoising—Old and new

    Moeller, M. & Cremers, D., 2018, Advances in Computer Vision and Pattern Recognition. Springer London, p. 63-91 29 p. (Advances in Computer Vision and Pattern Recognition).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    3 Scopus citations

  • Partial Single- and Multishape Dense Correspondence Using Functional Maps

    Litany, O., Rodolà, E., Bronstein, A., Bronstein, M. & Cremers, D., 2018, Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 1. Kimmel, R. & Tai, X.-C. (eds.). Elsevier B.V., p. 55-90 36 p. (Handbook of Numerical Analysis; vol. 19).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    1 Scopus citations
  • 2016

    Applying random forests to the problem of dense non-rigid shape correspondence

    Vestner, M., Rodolà, E., Windheuser, T., Bulò, S. R. & Cremers, D., 2016, Visualization in Medicine and Life Sciences III - Towards Making an Impact. Linsen, L., Hege, H.-C. & Hamann, B. (eds.). Springer Heidelberg, p. 231-248 18 p. (Mathematics and Visualization).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

  • Collision avoidance for quadrotors with a monocular camera

    Alvarez, H., Paz, L. M., Sturm, J. & Cremers, D., 2016, Springer Tracts in Advanced Robotics. Springer Verlag, p. 195-209 15 p. (Springer Tracts in Advanced Robotics; vol. 109).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    63 Scopus citations
  • 2015

    Image segmentation with shape priors: Explicit versus implicit representations

    Cremers, D., 1 Jan 2015, Handbook of Mathematical Methods in Imaging: Volume 1, Second Edition. Springer New York, p. 1909-1944 36 p.

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    6 Scopus citations

  • q-space deep learning for twelve-fold shorter and model-free diffusion MRI scans

    Golkov, V., Dosovitskiy, A., Sämann, P., Sperl, J. I., Sprenger, T., Czisch, M., Menzel, M. I., Gómez, P. A., Haase, A., Brox, T. & Cremers, D., 2015, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, p. 37-44 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9349).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    Open Access
    14 Scopus citations
  • 2013

    A sequential Monte Carlo method for multi-target tracking with the intensity filter

    Schikora, M., Koch, W., Streit, R. & Cremers, D., 2013, Advances in Intelligent Signal Processing and Data Mining: Theory and Applications. Springer Verlag, p. 55-87 33 p. (Studies in Computational Intelligence; vol. 410).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    15 Scopus citations
  • 2006

    Integral invariants and shape matching

    Manay, S., Cremers, D., Hong, B. W., Yezzi, A. & Soatto, S., 2006, Modeling and Simulation in Science, Engineering and Technology. 9780817643768 ed. Springer Basel, p. 137-166 30 p. (Modeling and Simulation in Science, Engineering and Technology; no. 9780817643768).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    12 Scopus citations

  • Probabilistic kernel PCA and its application to statistical modeling and inference

    Cremers, D. & Kohlberger, T., 2006, Kernel Methods in Bioengineering, Signal and Image Processing. IGI Global, p. 346-373 28 p.

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    1 Scopus citations

  • Variational segmentation with shape priors

    Bergtholdh, M., Cremers, D. & Schurr, C., 2006, Handbook of Mathematical Models in Computer Vision. Springer US, p. 131-143 13 p.

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

  • 2004

    Kernel density estimation and intrinsic alignment for knowledge-driven segmentation: teaching level sets to walk

    Cremers, D., Osher, S. J. & Soatto, S., 2004, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Rasmussen, C. E., Bulthoff, H. H., Scholkopf, B. & Giese, M. A. (eds.). Springer Verlag, p. 36-44 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 3175).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    46 Scopus citations

  • Multiphase dynamic labeling for variational recognition-driven image segmentation

    Cremers, D., Sochen, N. & Schnörr, C., 2004, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Pajdla, T. & Matas, J. (eds.). Springer Verlag, p. 74-86 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 3024).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    22 Scopus citations
  • 2003

    A generative model based approach to motion segmentation

    Cremers, D. & Yuille, A., 2003, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Michaelis, B. & Krell, G. (eds.). Springer Verlag, p. 313-320 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 2781).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    8 Scopus citations

  • A multiphase level set framework for motion segmentation

    Cremers, D., 2003, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Griffin, L. D. & Lillholm, M. (eds.). Springer Verlag, p. 599-614 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 2695).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    41 Scopus citations

  • Towards recognition-based variational segmentation using shape priors and dynamic labeling

    Cremers, D., Sochen, N. & Schnörr, C., 2003, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Griffin, L. D. & Lillholm, M. (eds.). Springer Verlag, p. 388-400 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 2695).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

    113 Scopus citations