Geometry in Machine Learning Group | University of Bonn and Lamarr Institute

SShaDe: a Framework for Scalable Shape Deformation via Local Representations

Filippo Maggioli, Daniele Baieri, Zorah Lähner, Simone Melzi
Published in arXiv:2409.17961, 2024
[arxiv] [bibtex]

Implicit-ARAP: Efficient Handle-Guided Deformation of High-Resolution Meshes and Neural Fields via Local Patch Meshing

Daniele Baieri, Filippo Maggioli, Zorah Lähner, Simone Melzi, Emanuele Rodolà
Published in arXiv:2405.12895, 2024
[arxiv] [bibtex]

Synchronous Diffusion for Unsupervised 3D Shape Matching

Dongliang Cao, Zorah Lähner, Florian Bernard
Published in European Conference on Computer Vision (ECCV), 2024
[bibtex]

3D Shape Completion with Test-Time Training

Michael Schopf-Kuester, Zorah Lähner, Michael Moeller
Published in ICML Workshop on Geometry-Grounded Representation Learning and Generative Modeling (GRaM), 2024
[bibtex]

Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching

Lennart Bastian, Yizheng Xie, Nassir Navab, Zorah Lähner
Published in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
[arxiv] [bibtex]

On the Direct Alignment of Latent Spaces

Zorah Lähner, Michael Moeller
Published in NeuRIPS Workshop on Unifying Representations in Neural Models (UniReps), 2023
[pdf] [bibtex]

Kissing to Find a Match: Efficient Low-Rank Permutation Representation

Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell, Felix Heide, Michael Moeller
Published in Neural Information Processing Systems (NeuRIPS), 2023
[pdf] [arxiv] [github] [bibtex]

SIGMA: Scale-Invariant Global Sparse Shape Matching

Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Moeller, Daniel Cremers, Florian Bernard
Published in International Conference on Computer Vision (ICCV), 2023
[pdf] [arxiv] [bibtex]

A Network Analysis for Correspondence Learning via Linearly-Embedded Functions

Sharik Siddiqi, Zorah Lähner
Published in German Conference on Pattern Recognition (GCPR), 2023
[pdf] [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]

QuAnt: Quantum Annealing with Learnt Couplings

Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner, Michael Moeller, Vladislav Golyanik
Published in International Conference on Learning Representations (ICLR), 2023
[pdf] [arxiv] [github] [bibtex]

A Simple Strategy to Make Neural Networks Provably Invariant

Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czapliński, Michael Moeller
Published in Asian Conference on Computer Vision (ACCV), 2022
[pdf] [arxiv] [bibtex]

Intrinsic Neural Fields: Learning Functions on Manifolds

Lukas Koestler, Daniel Grittner, Michael Moeller, Daniel Cremers, Zorah Lähner
Published in European Conference on Computer Vision (ECCV), 2022
[pdf] [arxiv] [github] [bibtex]

Light-Weight Learning-Based Depth Estimation From A Single Image

Zekarias Negese, Hartmut Bauermeister, Michael Moeller, Emanuele Rodolà, Zorah Lähner
Published in ATHENA Research Book, 2022
[pdf] [bibtex]

Continuous Correspondence of Non-Rigid 3D Shapes

Zorah Lähner
Published in TUM University Press, 2021
[pdf] [bibtex]

Systems and Methods for Generating Accurate and Realistic Clothing Models with Wrinkles

Tony Tung, Zorah Lähner
Published in US Patent 11158121, 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]

Isometric Multi-Shape Matching

Maolin Gao, Zorah Lähner, Johan Thunberg, Daniel Cremers, Florian Bernard
Published in Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[pdf] [arxiv] [github] [video] [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]

DeepWrinkles: Accurate and Realistic Clothing Modeling

Zorah Lähner, Daniel Cremers, Tony Tung
Published in European Conference on Computer Vision (ECCV), 2018
[pdf] [arxiv] [video] [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]

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