| Morphable face models-an open framework T Gerig, A Morel-Forster, C Blumer, B Egger, M Luthi, S Schönborn, ... 2018 13th IEEE international conference on automatic face & gesture …, 2018 | 300 | 2018 |
| Gaussian process morphable models M Lüthi, T Gerig, C Jud, T Vetter IEEE transactions on pattern analysis and machine intelligence 40 (8), 1860-1873, 2017 | 240 | 2017 |
| Analyzing and reducing the damage of dataset bias to face recognition with synthetic data A Kortylewski, B Egger, A Schneider, T Gerig, A Morel-Forster, T Vetter Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 140 | 2019 |
| Posterior shape models T Albrecht, M Lüthi, T Gerig, T Vetter Medical image analysis 17 (8), 959-973, 2013 | 100 | 2013 |
| Training deep face recognition systems with synthetic data A Kortylewski, A Schneider, T Gerig, B Egger, A Morel-Forster, T Vetter arXiv preprint arXiv:1802.05891, 2018 | 77 | 2018 |
| Empirically analyzing the effect of dataset biases on deep face recognition systems A Kortylewski, B Egger, A Schneider, T Gerig, A Morel-Forster, T Vetter Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 75 | 2018 |
| Spatially varying registration using Gaussian processes T Gerig, K Shahim, M Reyes, T Vetter, M Lüthi Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 28 | 2014 |
| Supervised learning for bone shape and cortical thickness estimation from CT images for finite element analysis V Chandran, G Maquer, T Gerig, P Zysset, M Reyes Medical image analysis 52, 42-55, 2019 | 26 | 2019 |
| Can synthetic faces undo the damage of dataset bias to face recognition and facial landmark detection? A Kortylewski, B Egger, A Morel-Forster, A Schneider, T Gerig, C Blumer, ... arXiv preprint arXiv:1811.08565, 2018 | 16* | 2018 |
| Shape modeling using gaussian process morphable models M Lüthi, A Forster, T Gerig, T Vetter Statistical shape and deformation analysis, 165-191, 2017 | 14 | 2017 |
| Probabilistic fitting of active shape models A Morel-Forster, T Gerig, M Lüthi, T Vetter Shape in Medical Imaging: International Workshop, ShapeMI 2018, Held in …, 2018 | 13 | 2018 |
| Error-controlled model approximation for Gaussian process morphable models J Dölz, T Gerig, M Lüthi, H Harbrecht, T Vetter Journal of Mathematical Imaging and Vision 61, 443-457, 2019 | 5 | 2019 |
| Gaussian process morphable models for spatially-varying multi-scale registration T Gerig University_of_Basel, 2021 | 3 | 2021 |
| Efficient computation of low-rank Gaussian process models for surface and image registration J Dölz, T Gerig, H Harbrecht, M Lüthi, T Vetter Universität Basel 2017 (01), 2017 | 2 | 2017 |
| Gaussian process morphable models for spatially-varying multi-scale registration: modeling and approximation T Gerig Philosophisch-Naturwissenschaftliche Fakultät der Universität Basel, 2021 | | 2021 |
Thomas VetterEmeritus Professor in Computer Science, University of Basel在 unibas.ch 的电子邮件经过验证
