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Technical University of Munich

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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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CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More


Geometry Processing

Geometry processing is concerned with the acquisition, analysis and manipulation of geometric data. The field is very broad and algorithms aim at improving 3D reconstructions, finding correspondences between objects, shape interpolation, or analysing physical properties of scanned data. Many applications in geometry processing have counterparts in image processing, e.g. object detection, but geometric data poses special challenges in terms of how to formulate mathematical concepts on discretized domains, and choosing the best data structures and shape representations for each application.

Our group is especially interested in 3D geometric data and works mainly in the directions of 3D shape analysis, point cloud processing and inference from 3D data. But our members have worked on a wide range of subtopics, so feel free to reach out to us if you are interested in any geometry processing related topic!

3D Shape Analysis Point Cloud Processing Inference from 3D data
Non-Rigid Correspondence
Non-Rigid Correspondence
Primitive Detection
Primitive Detection
Material Reconstruction
Material Reconstruction

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Sort Order:  by type by year
2020 2019 2018 2017 2016 2015 2013 
2020
Journal Articles
[]From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds (C. Sommer, Y. Sun, L. J. Guibas, D. Cremers and T. Birdal), In IEEE Robotics and Automation Letters (RA-L) & International Conference on Robotics and Automation (ICRA), volume 5, 2020.  [bibtex] [doi] [arXiv:2001.07360]
Conference and Workshop Papers
[]Unsupervised Dense Shape Correspondence using Heat Kernels (M Aygün, Z Lähner and D Cremers), In International Conference on 3D Vision (3DV), 2020.  [bibtex] [pdf]
[]Simulated Annealing for 3D Shape Correspondence (B Holzschuh, Z Lähner and D Cremers), In International Conference on 3D Vision (3DV), 2020.  [bibtex] [pdf]Oral Presentation
[]PrimiTect: Fast Continuous Hough Voting for Primitive Detection (C. Sommer, Y. Sun, E. Bylow and D. Cremers), In International Conference on Robotics and Automation (ICRA), 2020.  [bibtex] [doi] [arXiv:2005.07457]
[]Correspondence-Free Material Reconstruction using Sparse Surface Constraints (S. Weiss, R. Maier, D. Cremers, R. Westermann and N. Thuerey), In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2020.  [bibtex] [pdf]
[]Hamiltonian Dynamics for Real-World Shape Interpolation (M. Eisenberger and D. Cremers), In European Conference on Computer Vision (ECCV), 2020. ([arXiv] [code]) [bibtex]Spotlight Presentation
[]Smooth Shells: Multi-Scale Shape Registration with Functional Maps (M. Eisenberger, Z. Lähner and D. Cremers), In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2020. ([pdf] [arXiv] [code]) [bibtex]Oral Presentation
Other Publications
[]i3DMM: Deep Implicit 3D Morphable Model of Human Heads (T Yenamandra, A Tewari, F Bernard, HP Seidel, M Elgharib, D Cremers and C Theobalt), [project page], 2020. ([project page]) [bibtex]
2020 2019 2018 2017 2016 2015 2013 
2019
Journal Articles
[]Functional Maps Representation on Product Manifolds (E Rodolà, Z Lähner, AM. Bronstein, MM. Bronstein and J Solomon), In Computer Graphics Forum, volume 38, 2019. ((Presented at Symposium on Geometry Processing (SGP)) [arxiv]) [bibtex] [pdf]
Conference and Workshop Papers
[]Sparse Surface Constraints for Combining Physics-based Elasticity Simulation and Correspondence-Free Object Reconstruction (S. Weiss, R. Maier, R. Westermann, D. Cremers and N. Thuerey), In arXiv preprint arXiv:1910.01812, 2019. ([pdf]) [bibtex] [arXiv:1910.01812]
[]Divergence-Free Shape Correspondence by Deformation (M. Eisenberger, Z. Lähner and D. Cremers), In Computer Graphics Forum, volume 38, 2019. ([arxiv]) [bibtex] [pdf]
[]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]
2020 2019 2018 2017 2016 2015 2013 
2018
Conference and Workshop Papers
[]Robust Fitting of Subdivision Surfaces for Smooth Shape Analysis (V. Estellers, F. Schmidt and D. Cremers), In Proc. of the Int. Conference on 3D Vision (3DV), 2018. ([Code]) [bibtex] [pdf]Received the Best Paper Award at 3DV 2018
[]DeepWrinkles: Accurate and Realistic Clothing Modeling (Z. Lähner, D. Cremers and T. Tung), In European Conference on Computer Vision (ECCV), 2018. ([Homepage], [Oral Presentation]) [bibtex] [pdf]Oral Presentation
[]Joint Representation of Primitive and Non-primitive Objects for 3D Vision (C. Sommer and D. Cremers), In 2018 International Conference on 3D Vision, 3DV 2018, Verona, Italy, September 5-8, 2018, IEEE Computer Society, 2018.  [bibtex] [doi]
2020 2019 2018 2017 2016 2015 2013 
2017
Journal Articles
[]Regularized Pointwise Map Recovery from Functional Correspondence (E Rodolà, M Möller and D Cremers), In Comput. Graph. Forum, volume 36, 2017.  [bibtex]
Conference and Workshop Papers
[]A Combinatorial Solution to Non-Rigid 3D Shape-to-Image Matching (F. Bernard, F. R. Schmidt, J. Thunberg and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.  [bibtex] [pdf]
[]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]
2020 2019 2018 2017 2016 2015 2013 
2016
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]
Conference and Workshop Papers
[]A Convex Solution to Spatially-Regularized Correspondence Problems (T. Windheuser and D. Cremers), In European Conference on Computer Vision (ECCV), 2016.  [bibtex] [pdf]
[]Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding (I. Chiotellis, R. Triebel, T. Windheuser and D. Cremers), In European Conference on Computer Vision (ECCV), 2016. ([code]) [bibtex] [pdf]
[] SHREC’16: Matching of Deformable Shapes with Topological Noise (Z. Lähner, E. Rodola, M. M. Bronstein, D. Cremers, O. Burghard, L. Cosmo, A. Dieckmann, R. Klein and Y. Sahillioglu), In Proc. of Eurographics Workshop on 3D Object Retrieval (3DOR), 2016. ([Dataset]) [bibtex] [pdf] [pdf]
[] Efficient Globally Optimal 2D-to-3D Deformable Shape Matching (Z. Lähner, E. Rodola, F. R. Schmidt, M. M. Bronstein and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. ([Code], [Homepage]) [bibtex] [pdf] [pdf]
2020 2019 2018 2017 2016 2015 2013 
2015
Journal Articles
[]Fast and Accurate Surface Alignment through an Isometry-Enforcing Game (A. Albarelli, E. Rodola and A. Torsello), In Pattern Recognition, Elsevier, volume 48, 2015.  [bibtex] [doi] [pdf]
2020 2019 2018 2017 2016 2015 2013 
2013
Journal Articles
[]Stable and Fast Techniques for Unambiguous Compound Phase Coding (A. Torsello, A. Albarelli and E. Rodola), In Image and Vision Computing, volume 31, 2013.  [bibtex] [doi] [pdf]
[]A Scale Independent Selection Process for 3D Object Recognition in Cluttered Scenes (E. Rodola, A. Albarelli, F. Bergamasco and A. Torsello), In International Journal of Computer Vision, Springer US, volume 102, 2013.  [bibtex] [doi] [pdf]
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Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

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

Follow us on:
CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More