| Deepwrinkles: Accurate and realistic clothing modeling Z Lahner, D Cremers, T Tung Proceedings of the European conference on computer vision (ECCV), 667-684, 2018 | 216 | 2018 |
| 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 | 92 | 2017 |
| 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 | 91 | 2020 |
| 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 | 63 | 2016 |
| Divergence‐free shape correspondence by deformation M Eisenberger, Z Lähner, D Cremers Computer Graphics Forum 38 (5), 1-12, 2019 | 50 | 2019 |
| 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 | 33 | 2016 |
| 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 | 28 | 2021 |
| 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 | 27 | 2021 |
| 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 | 23 | 2019 |
| 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 | 21 | 2022 |
| Functional maps representation on product manifolds E Rodolà, Z Lähner, AM Bronstein, MM Bronstein, J Solomon Computer Graphics Forum 38 (1), 678-689, 2019 | 20 | 2019 |
| 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 | 20 | 2017 |
| 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 | 19 | 2017 |
| Simulated annealing for 3d shape correspondence B Holzschuh, Z Lähner, D Cremers 2020 International Conference on 3D Vision (3DV), 252-260, 2020 | 17 | 2020 |
| Unsupervised dense shape correspondence using heat kernels M Aygün, Z Lähner, D Cremers 2020 International Conference on 3D Vision (3DV), 573-582, 2020 | 15 | 2020 |
| 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 | 12 | 2017 |
| Systems and methods for generating accurate and realistic clothing models with wrinkles T Tung, Z Lähner US Patent 11,158,121, 2021 | 11 | 2021 |
| 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 | 9 | 2023 |
| 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 | 8 | 2021 |
| 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 | 7 | 2023 |
Daniel CremersTechnical University of Munich在 tum.de 的电子邮件经过验证
