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Zorah Lähner
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- affiliation: University of Bonn, Germany
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2020 – today
- 2024
- [c21]Lennart Bastian, Yizheng Xie, Nassir Navab, Zorah Lähner:
Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching. CVPR 2024: 3313-3323 - [i20]Daniele Baieri, Filippo Maggioli, Zorah Lähner, Simone Melzi, Emanuele Rodolà:
Implicit-ARAP: Efficient Handle-Guided Deformation of High-Resolution Meshes and Neural Fields via Local Patch Meshing. CoRR abs/2405.12895 (2024) - [i19]Dongliang Cao, Zorah Lähner, Florian Bernard:
Synchronous Diffusion for Unsupervised Smooth Non-Rigid 3D Shape Matching. CoRR abs/2407.08244 (2024) - 2023
- [c20]Harshil Bhatia, Edith Tretschk, Zorah Lähner
, Marcel Seelbach Benkner, Michael Moeller, Christian Theobalt, Vladislav Golyanik:
CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes. CVPR 2023: 1296-1305 - [c19]Paul Roetzer, Zorah Lähner
Conjugate Product Graphs for Globally Optimal 2D-3D Shape Matching. CVPR 2023: 21866-21875 - [c18]Sharik Siddiqi
A Network Analysis for Correspondence Learning via Linearly-Embedded Functions. DAGM 2023: 100-114 - [c17]Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Möller, Daniel Cremers, Florian Bernard:
ΣIGMA: Scale-Invariant Global Sparse Shape Matching. ICCV 2023: 645-654 - [c16]Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner, Michael Moeller, Vladislav Golyanik:
QuAnt: Quantum Annealing with Learnt Couplings. ICLR 2023 - [c15]Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell Nadal, Felix Heide, Michael Moeller:
Kissing to Find a Match: Efficient Low-Rank Permutation Representation. NeurIPS 2023 - [c14]Zorah Lähner, Michael Moeller:
On the Direct Alignment of Latent Spaces. UniReps 2023: 158-169 - [i18]Harshil Bhatia, Edith Tretschk, Zorah Lähner, Marcel Seelbach Benkner, Michael Moeller, Christian Theobalt
CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes. CoRR abs/2303.16202 (2023) - [i17]Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Möller, Daniel Cremers, Florian Bernard:
SIGMA: Scale-Invariant Global Sparse Shape Matching. CoRR abs/2308.08393 (2023) - [i16]Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell, Felix Heide, Michael Möller:
Kissing to Find a Match: Efficient Low-Rank Permutation Representation. CoRR abs/2308.13252 (2023) - [i15]Lennart Bastian, Yizheng Xie, Nassir Navab, Zorah Lähner:
Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching. CoRR abs/2312.03678 (2023) - 2022
- [c13]Kanchana Vaishnavi Gandikota
A Simple Strategy to Provable Invariance via Orbit Mapping. ACCV (5) 2022: 387-405 - [c12]Lukas Koestler, Daniel Grittner
Intrinsic Neural Fields: Learning Functions on Manifolds. ECCV (2) 2022: 622-639 - [i14]Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner:
Intrinsic Neural Fields: Learning Functions on Manifolds. CoRR abs/2203.07967 (2022) - [i13]Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller:
A Simple Strategy to Provable Invariance via Orbit Mapping. CoRR abs/2209.11916 (2022) - [i12]Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner, Michael Moeller, Vladislav Golyanik:
QuAnt: Quantum Annealing with Learnt Couplings. CoRR abs/2210.08114 (2022) - [i11]Paul Roetzer, Zorah Lähner, Florian Bernard:
Conjugate Product Graphs for Globally Optimal 2D-3D Shape Matching. CoRR abs/2211.11589 (2022) - 2021
- [b1]Zorah Lähner:
Continuous Correspondence of Non-Rigid 3D Shapes. Technical University of Munich, Germany, 2021 - [c11]Maolin Gao, Zorah Lähner
Isometric Multi-Shape Matching. CVPR 2021: 14183-14193 - [c10]Marcel Seelbach Benkner, Zorah Lähner
Q-Match: Iterative Shape Matching via Quantum Annealing. ICCV 2021: 7566-7576 - [i10]Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik, Christof Wunderlich, Christian Theobalt, Michael Möller:
Q-Match: Iterative Shape Matching via Quantum Annealing. CoRR abs/2105.02878 (2021) - [i9]Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller:
Training or Architecture? How to Incorporate Invariance in Neural Networks. CoRR abs/2106.10044 (2021) - 2020
- [c9]Benjamin Holzschuh, Zorah Lähner
Simulated Annealing for 3D Shape Correspondence. 3DV 2020: 252-260 - [c8]Mehmet Aygün, Zorah Lähner
Unsupervised Dense Shape Correspondence using Heat Kernels. 3DV 2020: 573-582 - [c7]Marvin Eisenberger, Zorah Lähner
Smooth Shells: Multi-Scale Shape Registration With Functional Maps. CVPR 2020: 12262-12271 - [i8]Mehmet Aygün, Zorah Lähner, Daniel Cremers:
Unsupervised Dense Shape Correspondence using Heat Kernels. CoRR abs/2010.12682 (2020) - [i7]Maolin Gao, Zorah Lähner, Johan Thunberg, Daniel Cremers, Florian Bernard:
Isometric Multi-Shape Matching. CoRR abs/2012.02689 (2020)
2010 – 2019
- 2019
- [j2]Emanuele Rodolà
Functional Maps Representation On Product Manifolds. Comput. Graph. Forum 38(1): 678-689 (2019) - [j1]Marvin Eisenberger
Divergence-Free Shape Correspondence by Deformation. Comput. Graph. Forum 38(5): 1-12 (2019) - [c6]Roberto M. Dyke
Shape Correspondence with Isometric and Non-Isometric Deformations. 3DOR@Eurographics 2019: 111-119 - [i6]Marvin Eisenberger, Zorah Lähner, Daniel Cremers:
Smooth Shells: Multi-Scale Shape Registration with Functional Maps. CoRR abs/1905.12512 (2019) - 2018
- [c5]Zorah Lähner
DeepWrinkles: Accurate and Realistic Clothing Modeling. ECCV (4) 2018: 698-715 - [c4]Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps on Product Manifolds. SGP (Posters) 2018: 9-10 - [i5]Marvin Eisenberger, Zorah Lähner, Daniel Cremers:
Divergence-Free Shape Interpolation and Correspondence. CoRR abs/1806.10417 (2018) - [i4]Zorah Lähner, Daniel Cremers, Tony Tung:
DeepWrinkles: Accurate and Realistic Clothing Modeling. CoRR abs/1808.03417 (2018) - [i3]Emanuele Rodolà, Zorah Lähner, Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps Representation on Product Manifolds. CoRR abs/1809.10940 (2018) - 2017
- [c3]Matthias Vestner, Zorah Lähner
Efficient Deformable Shape Correspondence via Kernel Matching. 3DV 2017: 517-526 - [i2]Zorah Lähner, Matthias Vestner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers:
Efficient Deformable Shape Correspondence via Kernel Matching. CoRR abs/1707.08991 (2017) - 2016
- [c2]Zorah Lähner
Matching of Deformable Shapes with Topological Noise. 3DOR@Eurographics 2016 - [c1]Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. CVPR 2016: 2185-2193 - [i1]Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers:
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. CoRR abs/1601.06070 (2016)
Coauthor Index
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