Non-Rigid Shape Correspondence
DFG Sachbeihilfeproject ‘Robust Spectral Non-Rigid Shape Correspondence’ (3 years)
Publications
Kissing to Find a Match: Efficient Low-Rank Permutation Representation
Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell, Felix Heide, Michael Moeller
Published in arXiv, 2023
[arxiv] [bibtex]
SIGMA: Scale-Invariant Global Sparse Shape Matching
Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Moeller, Daniel Cremers, Florian Bernard
Published in Accepted to International Conference on Computer Vision (ICCV), 2023
[bibtex]
A Network Analysis for Correspondence Learning via Linearly-Embedded Functions
Sharik Siddiqi, Zorah Lähner
Published in Accepted to German Conference on Pattern Recognition (GCPR), 2023
[bibtex]
Conjugate Product Graphs for Globally Optimal 2D-3D Shape Matching
Paul Roetzer, Zorah Lähner, Florian Bernard
Published in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
[pdf] [arxiv] [github] [bibtex]
CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes
Harshil Bhatia, Edith Tretschk, Zorah Lähner, Marcel Seelbach Benkner, Michael Moeller, Christian Theobalt, Vladislav Golyanik
Published in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
[pdf] [arxiv] [github] [bibtex]
Continuous Correspondence of Non-Rigid 3D Shapes
Zorah Lähner
Published in PhD Thesis, TUM University Press, 2021
[pdf] [bibtex]
Q-Match: Iterative Shape Matching via Quantum Annealing
Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik, Christof Wunderlich, Christian Theobalt, Michael Moeller
Published in International Conference on Computer Vision (ICCV), 2021
[pdf] [arxiv] [github] [bibtex]
Unsupervised Dense Shape Correspondence using Heat Kernels
Mehmet Aygün, Zorah Lähner, Daniel Cremers
Published in Conference on 3D Vision (3DV), 2020
[pdf] [arxiv] [bibtex]
Simulated Annealing for 3D Shape Correspondence
Benjamin Holzschuh, Zorah Lähner, Daniel Cremers
Published in Conference on 3D Vision (3DV), 2020
[pdf] [video] [bibtex]
Smooth Shells: Multi-Scale Shape Registration with Functional Maps
Marvin Eisenberger, Zorah Lähner, Daniel Cremers
Published in Conference on Computer Vision and Pattern Recognition (CVPR), 2020
[pdf] [arxiv] [github] [bibtex]
Functional Maps Representation on Product Manifolds
Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein, Michael M. Bronstein, Justin Solomon
Published in Computer Graphics Forum (CGF), 2019
[pdf] [arxiv] [bibtex]
Divergence-Free Shape Correspondence by Deformation
Marvin Eisenberger, Zorah Lähner, Daniel Cremers
Published in Symposium on Geometry Processing (SGP), 2019
[pdf] [arxiv] [bibtex]
Efficient Deformable Shape Correspondence via Kernel Matching
Matthias Vestner*, Zorah Lähner*, Amit Boyarski*, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronsteins, Ron Kimmel, Daniel Cremers
Published in International Conference on 3D Vision (3DV), 2017
[pdf] [arxiv] [github] [bibtex]
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching
Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers
Published in Conference on Computer Vision and Pattern Recognition (CVPR), 2016
[pdf] [arxiv] [github] [bibtex]
SHREC’16: Matching of Deformable Shapes with Topological Noise
Zorah Lähner, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers, Oliver Burghard, Luca Cosmo, Alexander Dieckmann, Reinhard Klein, Yusuf Sahillioğlu
Published in Eurographics Workshop on 3D Object Retrieval (3DOR), 2016
[pdf] [bibtex]