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Mathieu Salzmann
Mathieu Salzmann
EPFL
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Context-aware crowd counting
W Liu, M Salzmann, P Fua
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
7952019
Deep subspace clustering networks
P Ji, T Zhang, H Li, M Salzmann, I Reid
Advances in neural information processing systems 30, 2017
6792017
Learning to find good correspondences
KM Yi, E Trulls, Y Ono, V Lepetit, M Salzmann, P Fua
Proceedings of the IEEE conference on computer vision and pattern …, 2018
6632018
Beyond sharing weights for deep domain adaptation
A Rozantsev, M Salzmann, P Fua
IEEE transactions on pattern analysis and machine intelligence 41 (4), 801-814, 2018
5742018
Unsupervised Domain Adaptation by Domain Invariant Projection
M Baktashmotlagh, MT Harandi, BC Lovell, M Salzmann
International Conference on Computer Vision (ICCV), 2013
5582013
Learning trajectory dependencies for human motion prediction
W Mao, M Liu, M Salzmann, H Li
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
5432019
Learning the number of neurons in deep networks
JM Alvarez, M Salzmann
Advances in neural information processing systems 29, 2016
5152016
Discrete-continuous depth estimation from a single image
M Liu, M Salzmann, X He
Proceedings of the IEEE conference on computer vision and pattern …, 2014
4772014
Evaluating the search phase of neural architecture search
K Yu, C Sciuto, M Jaggi, C Musat, M Salzmann
arXiv preprint arXiv:1902.08142, 2019
4282019
Segmentation-driven 6d object pose estimation
Y Hu, J Hugonot, P Fua, M Salzmann
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
3872019
Kernel methods on the Riemannian manifold of symmetric positive definite matrices
S Jayasumana, R Hartley, M Salzmann, H Li, M Harandi
proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
3742013
Compression-aware training of deep networks
JM Alvarez, M Salzmann
Advances in neural information processing systems 30, 2017
3562017
History repeats itself: Human motion prediction via motion attention
W Mao, M Liu, M Salzmann
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
3552020
Structured prediction of 3d human pose with deep neural networks
B Tekin, I Katircioglu, M Salzmann, V Lepetit, P Fua
arXiv preprint arXiv:1605.05180, 2016
3482016
Learning to fuse 2d and 3d image cues for monocular body pose estimation
B Tekin, P Márquez-Neila, M Salzmann, P Fua
Proceedings of the IEEE international conference on computer vision, 3941-3950, 2017
3232017
Unsupervised geometry-aware representation for 3d human pose estimation
H Rhodin, M Salzmann, P Fua
Proceedings of the European conference on computer vision (ECCV), 750-767, 2018
3072018
Learning monocular 3d human pose estimation from multi-view images
H Rhodin, J Spörri, I Katircioglu, V Constantin, F Meyer, E Müller, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2018
2992018
Kernel methods on Riemannian manifolds with Gaussian RBF kernels
S Jayasumana, R Hartley, M Salzmann, H Li, M Harandi
IEEE transactions on pattern analysis and machine intelligence 37 (12), 2464 …, 2015
2972015
From manifold to manifold: Geometry-aware dimensionality reduction for SPD matrices
MT Harandi, M Salzmann, R Hartley
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
2462014
Single-stage 6d object pose estimation
Y Hu, P Fua, W Wang, M Salzmann
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
2402020
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Artikelen 1–20