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Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich



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Book Chapters
[]Applying Random Forests to the Problem of Dense Non-rigid Shape Correspondence (M. Vestner, E. Rodolà, T. Windheuser, RBS. Bulò and D. Cremers), Chapter in Perspectives in Shape Analysis, Springer, 2016.  [bibtex]
[]Bayesian Inference of Bijective Non-Rigid Shape Correspondence (M. Vestner, R. Litman, A. Bronstein, E. Rodola and D. Cremers), In arXiv preprint arXiv:1607.03425, 2016. ([slides]) [bibtex] [pdf]
Conference and Workshop Papers
[]Shape Correspondence with Isometric and Non-Isometric Deformations (R. Dyke, C. Stride, Y.-K. Lai, P. L. Rosin, M. Aubry, A. Boyarski, A. M. Bronstein, M. M. Bronstein, D. Cremers, M. Fisher, T. Groueix, D. Guo, V. G. Kim, R. Kimmel, Z. Lähner, K. Li, O. Litany, T. Remez, E. Rodolà, B. C. Russell, Y. Sahillioglu, R. Slossberg, G. K. L. Tam, M. Vestner, Z. Wu and J. Yang), In 12th Eurographics Workshop on 3D Object Retrieval, 3DOR@Eurographics 2019, Genoa, Italy, May 5-6, 2019 (S Biasotti, G Lavoué, RC. Veltkamp, eds.), Eurographics Association, 2019.  [bibtex]
[]Efficient Deformable Shape Correspondence via Kernel Matching (M. Vestner, Z. Lähner, A. Boyarski, O. Litany, R. Slossberg, T. Remez, E. Rodolà, A. M. Bronstein, M. M. Bronstein, R. Kimmel and D. Cremers), In International Conference on 3D Vision (3DV), 2017. ([arxiv],[Code]) [bibtex] [pdf]Oral Presentation
[]Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space (M. Vestner, R. Litman, E. Rodola, A. Bronstein and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. ([Code], also check the related github repository) [bibtex] [pdf]
[]Optimal Intrinsic Descriptors for Non-Rigid Shape Analysis (T. Windheuser, M. Vestner, E. Rodola, R. Triebel and D. Cremers), In British Machine Vision Conference (BMVC), 2014.  [bibtex] [pdf]
[]Dense Non-Rigid Shape Correspondence Using Random Forests (E. Rodola, S. R Bulo, T. Windheuser, M. Vestner and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.  [bibtex] [pdf] [code]
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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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In April 2022 Jürgen Sturm, Christian Kerl and Daniel Cremers were featured among the top 10 most influential scholars in robotics of the last decade.


We have open PhD and postdoc positions! To apply, please use our application form.


We have six papers accepted to CVPR 2022 in New Orleans!


We have two papers accepted to ICRA 2022 - congrats to Lukas von Stumberg, Qing Cheng and Niclas Zeller!