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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 (Vestner, M., Rodolà, E., Windheuser, T., Bulò, Rota Bulo, S. and Cremers, D.), Chapter in Perspectives in Shape Analysis, Springer, 2016.  [bibtex]
[]Bayesian Inference of Bijective Non-Rigid Shape Correspondence (Vestner, M., Litman, R., Bronstein, A., Rodola, E. and Cremers, D.), In arXiv preprint arXiv:1607.03425, 2016. ([slides]) [bibtex] [pdf]
Conference and Workshop Papers
[]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 (Vestner, M., Litman, R., Rodola, E., Bronstein, A. and Cremers, D.), 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. Rota 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