Mathieu Salzmann

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mathieu.salzmann@epfl.ch +41 21 693 81 92

EPFL IC IINFCOM CVLAB
BC 308 (Bâtiment BC)
Station 14
CH-1015 Lausanne

Site web: https://sin.epfl.ch
Unité: SIN-ENS

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Données administratives

Compétences

Computer Vision
Machine Learning

Publications

Publications

Conference Papers

  • Y. Hu, J. Hugonot, P. Fua and M. Salzmann Segmentation-driven 6D Object Pose Estimation Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, June 2019.
  • W. Liu, M. Salzmann and P. Fua Context-aware Crowd Counting Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, June 2019.
  • H. Rhodin, V. Constantin, I. Katircioglu, M. Salzmann and P. Fua Neural Scene Decomposition for Multi-Person Motion Capture Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, June 2019.
  • M. Baktashmotlagh, M. Faraki, T. Drummond and M. Salzmann Learning Factorized Representations for Open-set Domain Adaptation International Conference on Learning Representations (ICLR), New Orleans, LA, May 2019.
  • M. S. Aliakbarian, F. Saleh, M. Salzmann, B. Fernando, L. Petersson and L. Andersson VIENA2: A Driving Anticipation Dataset Asian Conference on Computer Vision (ACCV), Perth, Australia, December 2018.
  • K. Yu and M. Salzmann Statistically-motivated Second-order Pooling European Conference on Computer Vision (ECCV), Munich, Germany, September 2018.
  • Z. Dang, K. M. Yi, Y. Hu, F. Wang, P. Fua and M. Salzmann Eigendecomposition-free Training of Deep Networks with Zero Eigenvalue-based Losses European Conference on Computer Vision (ECCV), Munich, Germany, September 2018.
  • F. Saleh, M. S. Aliakbarian, M. Salzmann, L. Petersson and J. M. Alvarez Effective Use of Synthetic Data for Urban Scene Semantic Segmentation European Conference on Computer Vision (ECCV), Munich, Germany, September 2018.
  • H. Rhodin, M. Salzmann and P. Fua Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation (oral) European Conference on Computer Vision (ECCV), Munich, Germany, September 2018.
  • J. Bednarik, P. Fua and M. Salzmann Learning to Reconstruct Texture-less Deformable Surfaces International Conference on 3D Vision (3DV), Verona, Italy, September 2018.
  • K. Nakka and M. Salzmann Deep Attentional Structured Representation Learning for Visual Recognition British Machine Vision Conference (BMVC), Newcastle, UK, September 2018.
  • M. Kozinski, A. Mosinska, M. Salzmann and P. Fua Learning to Segment 3D Linear Structures Using Only 2D Annotations International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain, September 2018.
  • K. M. Yi, E. Trulls, Y. Ono, V. Lepetit, M. Salzmann and P. Fua Learning to Find Good Correspondences (oral) Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, June 2018.
  • H. Rhodin, J. Spoerri, I. Katircioglu, V. Constantin, F. Meyer, E. Mueller, M. Salzmann and P. Fua Learning Monocular 3D Human Pose Estimation From Multi-View Images (spotlight) Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, June 2018.
  • M. Liu, X. He and M. Salzmann Geometry-Aware Deep Network for Single-Image Novel View Synthesis Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, June 2018.
  • A. Rozantsev, M. Salzmann and P. Fua Residual Parameter Transfer for Deep Domain Adaptation Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, June 2018.
  • R. Bermudez Chacon, P. Marquez Neila, M. Salzmann and P. Fua A Domain-Adaptive Two-Stream U-Net for Electron Microscopy Image Segmentation International Symposium on Biomedical Imaging (ISBI), Washington, D.C., April 2018.
  • W. Zhuo, M. Salzmann, X. He and M. Liu 3D Box Proposal from a Monocular Image for Indoor Scenes AAAI Conference on Artificial Intelligence (AAAI), New Orleans, LA, February 2018.
  • J. M. Alvarez and M. Salzmann Compression-aware Training of Deep Networks Neural Information Processing Systems (NIPS), Long Beach, CA, December 2017.
  • P. Ji, T. Zhang, H. Li, M. Salzmann and I. Reid Deep Subspace Clustering Networks Neural Information Processing Systems (NIPS), Long Beach, CA, December 2017.
  • T. Probst, A. Fossati, M. Salzmann and L. Van Gool Efficient Model-free Anthropometry from Depth Data International Conference on 3D Vision (3DV), Qingdao, China, October 2017.
  • B. Tekin, P. Marquez Neila, M. Salzmann and P. Fua Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation International Conference on Computer Vision (ICCV), Venice, Italy, October 2017.
  • M. S. Aliakbarian, F. Saleh, M. Salzmann, B. Fernando, L. Petersson and L. Andersson Encouraging LSTMs to Anticipate Actions Very Early International Conference on Computer Vision (ICCV), Venice, Italy, October 2017.
  • F. Saleh, M. S. Aliakbarian, M. Salzmann, L. Petersson and J. M. Alvarez Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation International Conference on Computer Vision (ICCV), Venice, Italy, October 2017.
  • M. Harandi, M. Salzmann and R. Hartley Joint Dimensionality Reduction and Metric Learning: A Geometric Take International Conference on Machine Learning (ICML), Sydney, Australia, August 2017.
  • Z. Hayder, X. He and M. Salzmann Boundary-aware Instance Segmentation Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, July 2017.
  • A. Thalaiyasingam, A. Desmaison, R. Bunel, M. Salzmann, P. H. S. Torr and M. P. Kumar Efficient Linear Programming for Dense CRFs Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, July 2017.
  • W. Zhuo, M. Salzmann, X. He and M. Liu Indoor Scene Parsing with Instance Segmentation, Semantic Labeling and Support Relationship Inference Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, July 2017.
  • J. M. Alvarez and M. Salzmann Learning the Number of Neurons in Deep Networks Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016.
  • M. Liu, X. He and M. Salzmann Building Scene Models by Completing and Hallucinating Depth and Semantics European Conference on Computer Vision (ECCV), Amsterdam, Netherlands, October 2016.
  • F. Saleh, M. S. Ali Akbarian, M. Salzmann, L. Petersson, S. Gould and J. M. Alvarez Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation European Conference on Computer Vision (ECCV), Amsterdam, Netherlands, October 2016.
  • X. Wang, M. Salzmann, F. Wang and J. Zhao Template-free 3D Reconstruction of Poorly-textured Nonrigid Surfaces European Conference on Computer Vision (ECCV), Amsterdam, Netherlands, October 2016.
  • R. Bermudez Chacon, C. Becker, M. Salzmann and P. Fua Scalable Unsupervised Domain Adaptation for Electron Microscopy International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Athens, Greece, October 2016.
  • B. Tekin, I. Katircioglu, M. Salzmann, V. Lepetit and P. Fua Structured Prediction of 3D Human Pose with Deep Neural Networks (oral) British Machine Vision Conference (BMVC), York, UK, September 2016.
  • P. Ji, H. Li, M. Salzmann and Y. Zhong Robust Multi-body Feature Tracker: A Segmentation-free Approach (spotlight) Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, AZ, June 2016.
  • Z. Hayder, X. He and M. Salzmann Learning to Co-Generate Object Proposals with a Deep Structured Network Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, AZ, June 2016.
  • M. Harandi, M. Salzmann and F. Porikli When VLAD met Hilbert Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, AZ, June 2016.
  • M. Najafi, S. Taghavi Namin, M. Salzmann and L. Petersson Sample and Filter: Nonparametric Scene Parsing via Efficient Filtering Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, AZ, June 2016.
  • A. Thalaiyasingam, R. Hartley and M. Salzmann Memory Efficient Max Flow for Multi-label Submodular MRFs Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, AZ, June 2016.
  • J. M. Alvarez, M. Salzmann and N. Barnes Efficient Transductive Semantic Segmentation Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, March 2016.
  • A. Khan, S. Gould and M. Salzmann Segmentation of Developing Human Embryo in Time-Lapse Microscopy International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic, April 2016.
  • P. Ji, H. Li and M. Salzmann Shape Interaction Matrix Revisited and Robustified: Efficient Subspace Clustering with Corrupted and Incomplete Data (oral) International Conference on Computer Vision (ICCV), Santiago de Chile, December 2015.
  • M. Harandi, M. Salzmann and M. Baktashmotlagh Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs International Conference on Computer Vision (ICCV), Santiago de Chile, December 2015.
  • S. Taghavi Namin, M. Najafi, M. Salzmann and L. Petersson Cutting Edge: Soft Correspondences in Multimodal Scene Parsing International Conference on Computer Vision (ICCV), Santiago de Chile, December 2015.
  • W. Xu, M. Salzmann, Y. Wang and Y. Liu Deformable 3D Fusion: From Partial Dynamic 3D Observations to Complete 4D Models International Conference on Computer Vision (ICCV), Santiago de Chile, December 2015.
  • Z. Hayder, X. He and M. Salzmann Structural Kernel Learning for Large Scale Multiclass Object Co-Detection International Conference on Computer Vision (ICCV), Santiago de Chile, December 2015.
  • L. Horne, J. M. Alvarez, M. Salzmann and N. Barnes Efficient Scene Parsing by Sampling Unary Potentials in a Fully-Connected CRF Intelligent Vehicles Symposium (IV), Seoul, Korea, June 2015.
  • M. Harandi and M. Salzmann Riemannian Coding and Dictionary Learning: Kernels to the Rescue Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, June 2015. Supplementary material
  • W. Zhuo, M. Salzmann, X. He and M. Liu Indoor Scene Structure Analysis for Single Image Depth Estimation Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, June 2015.
  • A. Thalaiyasingam, R. Hartley, M. Salzmann and H. Li Iteratively Reweighted Graph Cut for Multi-label MRFs with Non-convex Priors Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, June 2015.
  • A. Khan, S. Gould and M. Salzmann Automated Monitoring of Human Embryonic Cells up to the 5-Cell Stage in Time-Lapse Microscopy Images International Symposium on Biomedical Imaging (ISBI), New York, NY, April 2015.
  • A. Khan, S. Gould and M. Salzmann A Linear Chain Markov Model for Detection and Localization of Cells in Early Stage Embryo Development Winter Conference on Applications of Computer Vision (WACV), Waikoloa Beach, HI, January 2015.
  • S. Taghavi Namin, M. Najafi, M. Salzmann and L. Petersson A Multi-modal Graphical Model for Scene Analysis Winter Conference on Applications of Computer Vision (WACV), Waikoloa Beach, HI, January 2015.
  • M. Harandi, M. Salzmann and R. Hartley From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices (oral) European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014. Supplementary material Code
  • M. Harandi, M. Salzmann, S. Jayasumana, R. Hartley and H. Li Expanding the Family of Grassmannian Kernels: An Embedding Perspective European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014. Supplementary material
  • Z. Hayder, M. Salzmann and X. He Object Co-Detection via Efficient Inference in a Fully-Connected CRF European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014.
  • P. Ji, H. Li, M. Salzmann and Y. Dai Robust Motion Segmentation with Unknown Correspondences European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014.
  • M. Najafi, S. Taghavi Namin, M. Salzmann and L. Petersson Non-Associative Higher-Order Markov Networks for Point Cloud Classification European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014.
  • W. Xu, M. Salzmann, Y. Wang and Y. Liu Nonrigid Surface Registration and Completion from RGBD Images European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014. Supplementary material
  • P. Ji, Y. Zhong, H. Li and M. Salzmann Null Space Clustering with Applications to Motion Segmentation and Face Clustering (best student paper award) International Conference on Image Processing (ICIP), Paris, France, October 2014.
  • S. Jayasumana, R. Hartley, M. Salzmann, H. Li and M. Harandi Optimizing Over Radial Kernels on Compact Manifolds (oral) Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, OH, June 2014.
  • M. Liu, M. Salzmann and X. He Discrete-Continuous Depth Estimation from a Single Image Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, OH, June 2014.
  • M. Harandi, M. Salzmann and F. Porikli Bregman Divergences for Infinite Dimensional Covariance Matrices Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, OH, June 2014. Supplementary material
  • M. Baktashmotlagh, M. Harandi, B. Lovell, and M. Salzmann Domain Adaptation on the Statistical Manifold Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, OH, June 2014.
  • J. M. Alvarez, M. Salzmann and N. Barnes Large-Scale Semantic Co-Labeling of Image Sets Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, CO, March 2014.
  • J. M. Alvarez, M. Salzmann and N. Barnes Data-Driven Road Detection Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, CO, March 2014.
  • P. Ji, M. Salzmann and H. Li Efficient Dense Subspace Clustering Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, CO, March 2014. Code
  • M. Baktashmotlagh, M. Harandi, B. Lovell and M. Salzmann Unsupervised Domain Adaptation by Domain Invariant Projection International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013.
  • S. Jayasumana, M. Salzmann, H. Li and M. Harandi A Framework for Shape Analysis via Hilbert Space Embedding International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013.
  • S. Jayasumana, R. Hartley, M. Salzmann, H. Li and M. Harandi Combining Multiple Manifold-valued Descriptors for Improved Object Recognition (CiSRA best recognition paper award) International Conference on Digital Image Computing: Techniques and Applications (DICTA), Hobart, Australia, November 2013.
  • M. Baktashmotlagh, M. Harandi, A. Bigdeli, B. Lovell and M. Salzmann Non-Linear Stationary Subspace Analysis with Application to Video Classification International Conference on Machine Learning (ICML), Atlanta, GA, June 2013. Supplementary material
  • M. Salzmann Continuous Inference in Graphical Models with Polynomial Energies Conference on Computer Vision and Pattern Recognition (CVPR), Portland, OR, June 2013. Code
  • S. Jayasumana, R. Hartley, M. Salzmann, H. Li and M. Harandi Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices (oral) Conference on Computer Vision and Pattern Recognition (CVPR), Portland, OR, June 2013.
  • M. Liu, R. Hartley and M. Salzmann Mirror Surface Reconstruction from a Single Image Conference on Computer Vision and Pattern Recognition (CVPR), Portland, OR, June 2013. Supplementary material
  • J. M. Alvarez, M. Salzmann and N. Barnes Learning Appearance Models for Road Detection Intelligent Vehicles Symposium (IV), Brisbane, Australia, June 2013.
  • M. Salzmann and R. Urtasun Beyond Feature Points: Structured Prediction for Monocular Non-rigid 3D Reconstruction European Conference on Computer Vision (ECCV), Firenze, Italy, October 2012.
  • A. Varol, M. Salzmann, P. Fua and R. Urtasun A Constrained Latent Variable Model Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, June 2012. Proofs
  • M. Brubaker, M. Salzmann and R. Urtasun A Family of MCMC Methods on Implicitly Defined Manifolds International Conference on Artificial Intelligence and Statistics (AISTATS), La Palma, Canary Islands, April 2012. Code
  • M. Salzmann and R. Urtasun Physically-based Motion Models for 3D Tracking: A Convex Formulation International Conference on Computer Vision (ICCV), Barcelona, November 2011.
  • Y. Jia, M. Salzmann and T. Darrell Learning Cross-modality Similarity for Multinomial Data International Conference on Computer Vision (ICCV), Barcelona, November 2011. Dataset
  • M. Salzmann and R. Urtasun Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation Neural Information Processing Systems Conference (NIPS), Vancouver, Canada, December 2010.
  • Y. Jia, M. Salzmann and T. Darrell Factorized Latent Spaces with Structured Sparsity Neural Information Processing Systems Conference (NIPS), Vancouver, Canada, December 2010.
  • C. M. Christoudias, R. Urtasun, M. Salzmann and T. Darrell Learning to Recognize Objects from Unseen Modalities European Conference on Computer Vision (ECCV), Heraklion, Crete, September 2010. Code dataset
  • M. Salzmann and R. Urtasun Combining Discriminative and Generative Methods for 3D Deformable Surface and Articulated Pose Reconstruction (oral) Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, June 2010.
  • M. Salzmann, C. H. Ek, R. Urtasun and T. Darrell Factorized Orthogonal Latent Spaces International Conference on Artificial Intelligence and Statistics (AISTATS), Sardinia, Italy, May 2010.
  • A. Varol, M. Salzmann, E. Tola and P. Fua Template-Free Monocular Reconstruction of Deformable Surfaces International Conference on Computer Vision (ICCV), Kyoto, Japan, October 2009.
  • M. Salzmann and P. Fua Reconstructing Sharply Folding Surfaces: A Convex Formulation (oral) Conference on Computer Vision and Pattern Recognition (CVPR), Miami, FL, June 2009. Code
  • F. Moreno-Noguer, M. Salzmann, V. Lepetit and P. Fua Capturing 3D Stretchable Surfaces from Single Images in Closed Form Conference on Computer Vision and Pattern Recognition (CVPR), Miami, FL, June 2009.
  • A. Fossati, M. Salzmann and P. Fua Observable Subspaces for 3D Human Motion Recovery Conference on Computer Vision and Pattern Recognition (CVPR), Miami, FL, June 2009.
  • M. Salzmann, F. Moreno-Noguer, V. Lepetit and P. Fua Closed-Form Solution to Non-Rigid 3D Surface Registration European Conference on Computer Vision (ECCV), Marseille, France, October 2008.
  • M. Salzmann, R. Urtasun and P. Fua Local Deformation Models for Monocular 3D Shape Recovery (oral) Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska, June 2008.
  • P. Lagger, M. Salzmann, V. Lepetit and P. Fua 3D Pose Refinement from Reflections (oral) Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska, June 2008.
  • M. Salzmann, R. Hartley and P. Fua Convex Optimization for Deformable Surface 3-D Tracking (oral) IEEE International Conference on Computer Vision (ICCV), Rio de Janeiro, Brazil, October 2007.
  • M. Salzmann, V. Lepetit and P. Fua Deformable Surface Tracking Ambiguities Conference on Computer Vision and Pattern Recognition (CVPR), Minneapolis, MI, June 2007.
  • M. Salzmann, S. Ilic and P. Fua Physically Valid Shape Parameterization for Monocular 3-D Deformable Surface Tracking British Machine Vision Conference (BMVC), Oxford Brookes, September 2005.
  • S. Ilic, M. Salzmann and P. Fua Implicit Surfaces Make for Better Silhouettes Conference on Computer Vision and Pattern Recognition (CVPR), San Diego, CA, June 2005.
  • Books and Book Chapters

  • M. Baktashmotlagh, M. Harandi and M. Salzmann Learning Domain Invariant Embeddings by Matching Distributions In Domain Adaptation in Computer Vision Applications, Springer 2017.
  • M. Harandi, R. Hartley, M. Salzmann and J. Trumpf Dictionary Learning on Grassmann Manifolds In Algorithmic Advances in Riemannian Geometry and Applications, Springer, 2016.
  • S. Jayasumana, R. Hartley and M. Salzmann Kernels on Riemannian Manifolds In Riemannian Computing in Computer Vision, Springer, 2016.
  • M. Salzmann and P. Fua Deformable Surface 3D Reconstruction from Monocular Images Morgan & Claypool, Synthesis Lectures on Computer Vision, 2010.
  • Journal Papers

  • A. Rozantsev, M. Salzmann and P. Fua Beyond Sharing Weights for Deep Domain Adaptation IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
  • F. Saleh, M. S. Ali Akbarian, M. Salzmann, L. Petersson, J. M. Alvarez and S. Gould Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018.
  • M. Harandi, M. Salzmann and R. Hartley Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.
  • J. M. Alvarez, M. Salzmann and N. Barnes Exploiting Large Image Sets for Road Scene Parsing IEEE Transactions on Intelligent Transportation Systems, Vol. 17, Nr. 9, pp. 2456-2465, September 2016.
  • M. Baktashmotlagh, M. Harandi and M. Salzmann Distribution-Matching Embedding for Visual Domain Adaptation Journal of Machine Learning Research (JMLR), Vol. 17, pp. 1-30, August 2016.
  • L. Horne, J. M. Alvarez, C. McCarthy, M. Salzmann and N. Barnes Semantic Labeling for Prosthetic Vision Computer Vision and Image Understanding, Vol. 149, pp. 113-125, August 2016.
  • S. Jayasumana, R. Hartley, M. Salzmann, H. Li and M. Harandi Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 37 , Nr. 12, pp. 2464-2477, December 2015.
  • M. Liu, R. Hartley and M. Salzmann Mirror Surface Reconstruction from a Single Image IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 37, Nr. 4, pp. 760-773, April 2015.
  • M. Baktashmotlagh, M. Harandi, B. Lovell and M. Salzmann Discriminative Non-Linear Stationary Subspace Analysis for Video Classification IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 36, Nr. 12, pp. 2353-2366, December 2014.
  • A. Varol, A. Shaji, M. Salzmann and P. Fua Monocular 3D Reconstruction of Locally Textured Surfaces IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 34, Nr. 6, pp. 1118-1130, June 2012.
  • M. Salzmann and P. Fua Linear Local Models for Monocular Reconstruction of Deformable Surfaces IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, Nr. 5, pp. 931-944, May 2011.
  • M. Salzmann, J.Pilet, S.Ilic and P.Fua Surface Deformation Models for Non-Rigid 3-D Shape Recovery IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, Nr. 8, pp. 1481 - 1487, August 2007.
  • S. Ilic, M. Salzmann and P. Fua Implicit Meshes for Effective Silhouette Handling International Journal of Computer Vision, Vol. 72, Nr. 2, pp. 159 - 178, 2007.
  • Workshops

  • A. Khan, S. Gould and M. Salzmann Deep Convolutional Neural Networks for Human Embryonic Cell Counting BioImage Computing, in conjunction with ECCV, October 2016.
  • A. Khan, S. Gould and M. Salzmann Detecting Abnormal Cell Division Patterns in Early Stage Human Embryo Development Machine Learning in Medical Imaging, in conjunction with MICCAI, October 2015.
  • A. Varol, M. Salzmann, P. Fua and R. Urtasun Constrained Regression for 3D Pose Estimation Learning Workshop (Snowbird), April 2011.
  • M. Salzmann, C. H. Ek, R. Urtasun and T. Darrell FOLS: Factorized Orthogonal Latent Spaces (oral) Learning Workshop (Snowbird), April 2010.
  • M. Salzmann and R. Urtasun A Constrained Combination of Discriminative and Generative Methods Learning Workshop (Snowbird), April 2010.
  • Technical Reports

  • M. Salzmann, J.Pilet, S.Ilic, P.Fua Parameterizing Deformable Surfaces for Monocular 3-D Tracking EPFL Technical Report IC/2005/020, 2005.
  • R. Urtasun, M. Salzmann, P. Fua 3D Morphing without User Interaction Technical Report, 2004.
  • Ph.D Thesis

  • M. Salzmann Learning and Recovering 3D Surface Deformations EPFL Thesis N° 4270, January 2009.