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Zorah Lähner
Zorah Lähner
Assistant Professor, University of Bonn
Verified email at uni-bonn.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
2292018
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
1002020
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
952017
SHREC'16: Matching of deformable shapes with topological noise
Z Lähner, E Rodolà, MM Bronstein, D Cremers, O Burghard, L Cosmo, ...
Eurographics Workshop on 3D Object Retrieval, EG 3DOR, 55-60, 2016
682016
Divergence‐free shape correspondence by deformation
M Eisenberger, Z Lähner, D Cremers
Computer Graphics Forum 38 (5), 1-12, 2019
512019
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
342016
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
312021
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
302021
SHREC-19: shape correspondence with isometric and non-isometric deformations
R Dyke, C Stride, Y Lai, P Rosin
242019
Intrinsic neural fields: Learning functions on manifolds
L Koestler, D Grittner, M Moeller, D Cremers, Z Lähner
European Conference on Computer Vision, 622-639, 2022
222022
Functional maps representation on product manifolds
E Rodolà, Z Lähner, AM Bronstein, MM Bronstein, J Solomon
Computer Graphics Forum 38 (1), 678-689, 2019
222019
Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodola, Alex Bronstein, Michael Bronstein, Ron Kimmel, et al. Efficient deformable shape correspondence via kernel matching
M Vestner, Z Lähner, A Boyarski
3D Vision (3DV), 2017 International Conference on, 517-526, 2017
202017
Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodola, Alex Bronstein, Michael Bronstein, Ron Kimmel, and Daniel Cremers. Efficient deformable shape correspondence via kernel …
M Vestner, Z Lähner, A Boyarski
Proc. 3DV 8, 14, 2017
202017
Simulated annealing for 3d shape correspondence
B Holzschuh, Z Lähner, D Cremers
2020 International Conference on 3D Vision (3DV), 252-260, 2020
172020
Unsupervised dense shape correspondence using heat kernels
M Aygün, Z Lähner, D Cremers
2020 International Conference on 3D Vision (3DV), 573-582, 2020
172020
On the direct alignment of latent spaces
Z Lähner, M Moeller
Proceedings of UniReps: the First Workshop on Unifying Representations in …, 2024
142024
Systems and methods for generating accurate and realistic clothing models with wrinkles
T Tung, Z Lähner
US Patent 11,158,121, 2021
142021
Ccuantumm: Cycle-consistent quantum-hybrid matching of multiple shapes
H Bhatia, E Tretschk, Z Lähner, MS Benkner, M Moeller, C Theobalt, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
122023
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
122017
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
92021
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Articles 1–20