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Zorah Lähner
Zorah Lähner
Postdoctoral Researcher, University of Siegen
Verified email at uni-siegen.de - Homepage
Title
Cited by
Cited by
Year
Deepwrinkles: Accurate and realistic clothing modeling
Z Lahner, D Cremers, T Tung
Proceedings of the European conference on computer vision (ECCV), 667-684, 2018
1342018
Efficient deformable shape correspondence via kernel matching
M Vestner, Z Lähner, A Boyarski, O Litany, R Slossberg, T Remez, ...
2017 International Conference on 3D Vision (3DV), 517-526, 2017
632017
SHREC’16: Matching of deformable shapes with topological noise
Z Lähner, E Rodola, MM Bronstein, D Cremers, O Burghard, L Cosmo, ...
Proc. 3DOR 2 (10.2312), 2016
382016
Smooth shells: Multi-scale shape registration with functional maps
M Eisenberger, Z Lahner, D Cremers
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
272020
Efficient globally optimal 2d-to-3d deformable shape matching
Z Lahner, E Rodola, FR Schmidt, MM Bronstein, D Cremers
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
242016
Efficient deformable shape correspondence via kernel matching
A Boyarski, A Bronstein, M Bronstein, D Cremers, R Kimmel, Z Lähner, ...
arXiv preprint arXiv 1707, 2017
20*2017
Divergence‐Free Shape Correspondence by Deformation
M Eisenberger, Z Lähner, D Cremers
Computer Graphics Forum 38 (5), 1-12, 2019
19*2019
Efficient deformable shape correspondence via kernel matching
Z Lähner, M Vestner, A Boyarski, O Litany, R Slossberg, T Remez, ...
arXiv preprint arXiv:1707.08991, 2017
18*2017
Shape correspondence with isometric and non-isometric deformations
RM Dyke, C Stride, YK Lai, PL Rosin, M Aubry, A Boyarski, AM Bronstein, ...
The Eurographics Association, 2019
13*2019
Functional maps representation on product manifolds
E Rodolà, Z Lähner, AM Bronstein, MM Bronstein, J Solomon
Computer Graphics Forum 38 (1), 678-689, 2019
122019
Efficient deformable shape correspondence via kernel matching
Z Lähner, M Vestner, A Boyarski, O Litany, R Slossberg, T Remez, ...
arXiv preprint arXiv:1707.08991, 2017
112017
Isometric multi-shape matching
M Gao, Z Lahner, J Thunberg, D Cremers, F Bernard
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
72021
Simulated annealing for 3d shape correspondence
B Holzschuh, Z Lähner, D Cremers
2020 International Conference on 3D Vision (3DV), 252-260, 2020
72020
Q-match: Iterative shape matching via quantum annealing
MS Benkner, Z Lähner, V Golyanik, C Wunderlich, C Theobalt, M Moeller
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
62021
Unsupervised dense shape correspondence using heat kernels
M Aygün, Z Lähner, D Cremers
2020 International Conference on 3D Vision (3DV), 573-582, 2020
52020
Training or Architecture? How to Incorporate Invariance in Neural Networks
KV Gandikota, J Geiping, Z Lähner, A Czapliński, M Moeller
arXiv preprint arXiv:2106.10044, 2021
22021
Intrinsic neural fields: Learning functions on manifolds
L Koestler, D Grittner, M Moeller, D Cremers, Z Lähner
arXiv preprint arXiv:2203.07967, 2022
12022
Systems and methods for generating accurate and realistic clothing models with wrinkles
T Tung, Z Lähner
US Patent 11,158,121, 2021
12021
Training or Architecture? How to Incorporate Invariance in Neural Networks
K Vaishnavi Gandikota, J Geiping, Z Lähner, A Czapliński, M Moeller
arXiv e-prints, arXiv: 2106.10044, 2021
2021
Continuous Correspondence of Non-Rigid 3D Shapes.
Z Lähner
Technical University of Munich, Germany, 2021
2021
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