Direkt zum Inhalt springen
Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich

Menu
Home Members Matthias Vestner

This is an old revision of the document!


Matthias Vestner

AlumniTechnische Universität München

Department of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
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. From October 2017 until April 2018 Matthias did an internship at the Intel Visual Computing Lab under the supervision of Vladlen Koltun and René Ranftl. From April until Oktober 2018 he did an internship at Apple.

Research Interests

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


Publications


Export as PDF, TEX or BIB

Book Chapters
2016
[]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]
Preprints
2016
[]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
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 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]
2014
[]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]
Powered by bibtexbrowser
Export as PDF, TEX or BIB


Teaching

Lectures and Seminars

Winter 2018 - Seminar
Shape Analysis and Optimization (IN2107)
Seminar for computer science master students and mathematics master students (2h / 4 ECTS).

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 of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching

info@vision.in.tum.de