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Technical University of Munich

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Home Members Matthias Vestner

Matthias Vestner

PhD StudentTechnische Universität München

Department of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching
Germany

Tel: +49-89-289-17753
Fax: +49-89-289-17757
Office: 02.09.058
Mail: matthias.vestner@in.tum.de

Brief Bio

Matthias has joined the Research Group for Computer Vision and Pattern Recognition as a Ph.D. student in June 2013.

In spring 2015 he spent three month at the group of Prof. Alexander Bronstein at Tel Aviv University.

In October 2017 Matthias has started an internship at the Intel Visual Computing Lab under the supervision of Vladlen Koltun and René Ranftl.

Matthias received his diploma in Mathematics from Technische Universität München in 2013.

Research Interests

Non-Rigid Shape Analysis, Reconstruction, (Discrete) Differential Geometry, Variational Methods, Functional Analysis


Publications

Book Chapters
2016
Applying Random Forests to the Problem of Dense Non-rigid Shape Correspondence (M. Vestner, E. Rodolà, T. Windheuser, Rota Bulo S. Bulò, D. Cremers), Chapter in Perspectives in Shape Analysis, Springertopic=Shape Analysis, Shape Matching, Machine Learning, 2016. [bib]
Journal Articles
2016
Bayesian Inference of Bijective Non-Rigid Shape Correspondence (M. Vestner, R. Litman, A. Bronstein, E. Rodola, D. Cremers), In arXiv preprint arXiv:1607.03425, 2016.([slides]) [bib] [pdf]
Conference and Workshop Papers
2017
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, D. Cremers), In International Conference on 3D Vision (3DV), 2017.([arxiv],[Code]) [bib] [pdf]
Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space (M. Vestner, R. Litman, E. Rodola, A. Bronstein, D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.([Code]) [bib] [pdf]
2014
Optimal Intrinsic Descriptors for Non-Rigid Shape Analysis (T. Windheuser, M. Vestner, E. Rodola, R. Triebel, D. Cremers), In British Machine Vision Conference (BMVC), 2014. [bib] [pdf]
Dense Non-Rigid Shape Correspondence Using Random Forests (E. Rodola, S. Rota Bulo, T. Windheuser, M. Vestner, D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. [bib] [pdf] [code]
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Teaching

Lectures and Seminars

Summer 2017 - Lecture
Analysis of Three-Dimensional Shapes (IN2238)
Lecture for computer science master students (4h + 2h / 8 ECTS).

Winter 2016 - Seminar
Recent Advances in the Analysis of 3D Shapes (IN2107)
Seminar for computer science master students and mathematics bachelor and master students (2h / 4 ECTS).

Summer 2016 - Lecture
Analysis of Three-Dimensional Shapes (IN2238)
Lecture for computer science master students (4h + 2h / 8 ECTS).

Summer 2016 - Seminar
Recent Advances in the Analysis of 3D Shapes (IN2107)
Seminar for computer science master students and mathematics bachelor and master students (2h / 4 ECTS).

Summer 2015 - Lecture
Analysis of Three-Dimensional Shapes (IN2238)
Lecture for computer science master students (4h + 2h / 8 ECTS).

Summer 2015 - Seminar
Recent Advances in the Analysis of 3D Shapes (IN2107)
Seminar for computer science master students and mathematics bachelor and master students (2h / 4 ECTS).

Summer 2014 - Lecture (tutorials)
Analysis of Three-Dimensional Shapes (IN2238)
Lecture for computer science master students (2h + 1h / 4 ECTS).

Summer 2014 - Seminar
Recent Advances in the Analysis of 3D Shapes (IN2107)
Seminar for computer science master students and mathematics bachelor and master students (2h / 4 ECTS).

Winter 2013/2014 - Lecture (tutorials)
Machine Learning for Robotics and Computer Vision (IN3200)
Lecture for computer science master students (2h + 1h / 4 ECTS).

Bachelor/Master's Theses and Interdisciplinary Projects (IDP)

I offer Bachelor's and Master's theses as well as IDPs for Mathematics and Computer Science students on topics related to 3D Shape Analysis. I highly recommend to attend our yearly (Summer semester) lecture and/or seminar on 3D shape analysis before starting the thesis. Possible topics include

  • Intrinsic symmetry detection
  • Shape Analysis on point clouds
  • Comparison of discrete representations of shapes
  • Partial similarity between shapes
  • Analysis of shape collections
  • Global description of 3D shapes
  • Discrete representations of 3D shapes
  • Partial Differential Equations on 3D shapes
  • Image processing on manifolds
  • Interpreting correspondences as maps between function spaces
  • Applying Machine Learning Techniques to 3D shape analysis

You are of course invited to propose your own topic.

Successfully defended works include:

29.04.2016
Thomas Ströhle (Mathematics, MS)
“Discrete Laplace-Beltrami Operators on Point Clouds”
23.10.2015
Zorah Lähner (Computer Science, MS)
“The Space of Functional Maps”
07.10.2015
Thorsten Philipp (Mathematics, MS)
“Learning Descriptors for Non-Rigid 3D Shapes”



Rechte Seite

Informatik IX
Chair for Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching

info@vision.in.tum.de