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Zorah Lähner
Zorah Lähner
Assistant Professor, University of Bonn
Dirección de correo verificada de uni-bonn.de - Página principal
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Año
Deepwrinkles: Accurate and realistic clothing modeling
Z Lahner, D Cremers, T Tung
Proceedings of the European conference on computer vision (ECCV), 667-684, 2018
2222018
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
932017
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
922020
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
662016
Divergence‐free shape correspondence by deformation
M Eisenberger, Z Lähner, D Cremers
Computer Graphics Forum 38 (5), 1-12, 2019
502019
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
282021
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
282021
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
242019
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
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
212022
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
192017
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
152020
Systems and methods for generating accurate and realistic clothing models with wrinkles
T Tung, Z Lähner
US Patent 11,158,121, 2021
132021
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
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
102023
Conjugate product graphs for globally optimal 2d-3d shape matching
P Roetzer, Z Lähner, F Bernard
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
82023
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
82021
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20