Andreas Morel-Forster
Andreas Morel-Forster
Postdoctoral Researcher, Department for Mathematics and Computer Science, University of Basel
Verified email at unibas.ch
Title
Cited by
Cited by
Year
Shape Modeling Using Gaussian Process Morphable Models
M Lüthi, A Forster, T Gerig, T Vetter
Statistical Shape and Deformation Analysis: Methods, Implementation and …, 2017
126*2017
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
992018
Markov chain monte carlo for automated face image analysis
S Schönborn, B Egger, A Morel-Forster, T Vetter
International Journal of Computer Vision 123 (2), 160-183, 2017
482017
Occlusion-aware 3d morphable models and an illumination prior for face image analysis
B Egger, S Schönborn, A Schneider, A Kortylewski, A Morel-Forster, ...
International Journal of Computer Vision 126 (12), 1269-1287, 2018
372018
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
342019
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
322018
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
272018
A monte carlo strategy to integrate detection and model-based face analysis
S Schönborn, A Forster, B Egger, T Vetter
German Conference on Pattern Recognition, 101-110, 2013
252013
Background modeling for generative image models
S Schönborn, B Egger, A Forster, T Vetter
Computer Vision and Image Understanding 136, 117-127, 2015
162015
Occlusion-aware 3D Morphable Face Models.
B Egger, A Schneider, C Blumer, A Forster, S Schönborn, T Vetter
BMVC 2, 4, 2016
122016
Pose normalization for eye gaze estimation and facial attribute description from still images
B Egger, S Schönborn, A Forster, T Vetter
German conference on pattern recognition, 317-327, 2014
122014
Greedy structure learning of hierarchical compositional models
A Kortylewski, A Wieczorek, M Wieser, C Blumer, S Parbhoo, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
112019
Pelletizing die with even heat distribution and with polymer channel to orifice transition zone, process for orifice thermal stabilization and process for forming a pelletizing …
CT Knight, JB Corry, J Blum, A Grundmann, D Bormann, A Forster
US Patent 6,976,834, 2005
112005
Human face shape analysis under spherical harmonics illumination considering self occlusion
J Zivanov, A Forster, S Schönborn, T Vetter
2013 International Conference on Biometrics (ICB), 1-8, 2013
102013
Generative shape and image analysis by combining Gaussian processes and MCMC sampling
A Morel-Forster
University_of_Basel, 2016
62016
Informed MCMC with Bayesian neural networks for facial image analysis
A Kortylewski, M Wieser, A Morel-Forster, A Wieczorek, S Parbhoo, ...
arXiv preprint arXiv:1811.07969, 2018
52018
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
5*2018
Probabilistic fitting of active shape models
A Morel-Forster, T Gerig, M Lüthi, T Vetter
International Workshop on Shape in Medical Imaging, 137-146, 2018
42018
A closest point proposal for MCMC-based probabilistic surface registration
D Madsen, A Morel-Forster, P Kahr, D Rahbani, T Vetter, M Lüthi
European Conference on Computer Vision, 281-296, 2020
32020
Greedy compositional clustering for unsupervised learning of hierarchical compositional models
A Kortylewski, C Blumer, T Vetter
arXiv preprint arXiv:1701.06171 73, 100, 2017
32017
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Articles 1–20