| Unsupervised Domain Adaptation by Domain Invariant Projection M Baktashmotlagh, MT Harandi, BC Lovell, M Salzmann International Conference on Computer Vision (ICCV), 2013 | 316 | 2013 |
| 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 | 271 | 2014 |
| 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 | 266 | 2013 |
| Learning the number of neurons in deep networks JM Alvarez, M Salzmann Advances in Neural Information Processing Systems, 2270-2278, 2016 | 239 | 2016 |
| 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 | 217 | 2018 |
| Learning cross-modality similarity for multinomial data Y Jia, M Salzmann, T Darrell 2011 International Conference on Computer Vision, 2407-2414, 2011 | 191 | 2011 |
| Factorized latent spaces with structured sparsity Y Jia, M Salzmann, T Darrell Advances in Neural Information Processing Systems, 982-990, 2010 | 178 | 2010 |
| Deep subspace clustering networks P Ji, T Zhang, H Li, M Salzmann, I Reid Advances in Neural Information Processing Systems, 24-33, 2017 | 160 | 2017 |
| From manifold to manifold: Geometry-aware dimensionality reduction for SPD matrices MT Harandi, M Salzmann, R Hartley European conference on computer vision, 17-32, 2014 | 160 | 2014 |
| 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 | 156 | 2016 |
| 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 | 138 | 2017 |
| Convex optimization for deformable surface 3-d tracking M Salzmann, R Hartley, P Fua 2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007 | 134 | 2007 |
| Surface deformation models for nonrigid 3D shape recovery M Salzmann, J Pilet, S Ilic, P Fua IEEE Transactions on Pattern Analysis and Machine Intelligence 29 (8), 1481-1487, 2007 | 134 | 2007 |
| 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 | 129 | 2015 |
| Local deformation models for monocular 3D shape recovery M Salzmann, R Urtasun, P Fua 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008 | 127 | 2008 |
| Learning to find good correspondences K Moo Yi, E Trulls, Y Ono, V Lepetit, M Salzmann, P Fua Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 110 | 2018 |
| Dimensionality reduction on SPD manifolds: The emergence of geometry-aware methods M Harandi, M Salzmann, R Hartley IEEE transactions on pattern analysis and machine intelligence 40 (1), 48-62, 2017 | 110 | 2017 |
| Closed-form solution to non-rigid 3D surface registration M Salzmann, F Moreno-Noguer, V Lepetit, P Fua European conference on computer vision, 581-594, 2008 | 110 | 2008 |
| Compression-aware training of deep networks JM Alvarez, M Salzmann Advances in Neural Information Processing Systems, 856-867, 2017 | 107 | 2017 |
| Linear local models for monocular reconstruction of deformable surfaces M Salzmann, P Fua IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (5), 931-944, 2010 | 106 | 2010 |
Pascal FuaProfessor Computer Science, EPFLVerified email at epfl.ch
