2013

• A. Geiger, M. Lauer, C. Wojek, C. Stiller and R. Urtasun.
  3D Traffic Scene Understanding from Movable Platforms
  In Pattern Analysis and Machine Intelligence (PAMI) 2013


• A. Geiger, P. Lenz, C. Stiller and R. Urtasun.
  Vision meets Robotics: The KITTI Dataset
  In International Journal of Robotics Research, (IJRR) 2013


• W. Luo, A. Schwing and R. Urtasun
  Latent Structured Active Learning [pdf]
  In Neural Information Processing Systems (NIPS), Lake Tahoe, USA, December 2013


• D. Lin, S. Fidler and R. Urtasun
  Holistic Scene Understanding for 3D Object Detection with RGBD cameras [pdf]   (oral)
  In International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013


• A. Schwing, S. Fidler, M. Pollefeys and R. Urtasun
  Box In the Box: Joint 3D Layout and Object Reasoning from Single Images [pdf]
  In International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013


• H. Zhang, A. Geiger and R. Urtasun
  Understanding High-Level Semantics by Modeling Traffic Patterns [pdf]
  In International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013


• J. Zhang, K. Chen, A. Schwing and R. Urtasun
  Estimating the 3D Layout of Indoor Scenes and its Clutter from Depth Sensors [pdf]
  In International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013


• M. Brubaker, A. Geiger and R. Urtasun
  Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization [pdf]    (oral, best paper runner up award)
  In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013


• K. Yamaguchi, D. McAllester and R. Urtasun
  Robust Monocular Epipolar Flow Estimation [pdf] (oral)
  In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013


• S. Fidler, R. Mottaghi, A. Yuille and R. Urtasun
  Bottom-up Segmentation for Top-down Detection [pdf]
  In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013


• S. Fidler, A. Sharma and R. Urtasun
  A Sentence is Worth a Thousand Pixels [pdf]
  In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013


• R. Mottaghi, S. Fidler, J. Yao, R. Urtasun and D. Parikh
  Analyzing Semantic Segmentation Using Human-Machine Hybrid CRFs [pdf]
  In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013

2012

• S. Fidler, S. Dickinson and R. Urtasun
  3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model  (spotlight)
  In Neural Information Processing Systems (NIPS), Lake Tahoe, USA, December 2012


• A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
  Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins
  In Neural Information Processing Systems (NIPS), Lake Tahoe, USA, December 2012


• K. Yamaguchi, T. Hazan, D. McAllester and R. Urtasun
  Continuous Markov Random Fields for Robust Stereo Estimation  (oral)
  In European Conference on Computer Vision (ECCV), Florence, Italy, October 2012


• A. Schwing and R. Urtasun
  Efficient Exact Inference for 3D Indoor Scene Understanding
  In European Conference on Computer Vision (ECCV), Florence, Italy, October 2012


• M. Salzmann and R. Urtasun
  Beyond Feature Points: Structured Prediction for Monocular Non-rigid 3D Reconstruction
  In European Conference on Computer Vision (ECCV), Florence, Italy, October 2012


• A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
  Efficient Structured Prediction with Latent Variables for General Graphical Models  (oral)
  In International Conference on Machine Learning (ICML), Edimburgh, Scotland, June 2012


• A. Geiger, P. Lenz and R. Urtasun
  Are we ready for autonomous driving? The KITTI Vision Benchmark Suite [pdf] [project page] (oral)
  In Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012


• J. Yao, S. Fidler and R. Urtasun
  Describing the Scene as a Whole: Joint Object Detection, Scene Classification and Semantic Segmentation
  In Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012


• A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
  Efficient Structured Prediction for 3D Indoor Scene Understanding
  In Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012


• A. Varol, M. Salzmann, P. Fua and R. Urtasun
  A Constrained Latent Variable Model
  In Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012


• M. Brubaker, M. Salzmann and R. Urtasun
  A Family of MCMC Methods on Implicitly Defined Manifolds
  In International Conference on Artificial Intelligence and Statistics (AISTATS), Gran Canaria, Spain, April 2012

2011

• A. Geiger, C. Wojek and R. Urtasun
  Joint 3D Estimation of Objects and Scene Layout [pdf] [supplementary] [video]
  In Neural Information Processing Systems (NIPS), Granada, Spain, December 2011


• A. Yao, J. Gall, L. van Gool and R. Urtasun
  Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities [pdf] [video learning] [video humaneva] [software]
  In Neural Information Processing Systems (NIPS), Granada, Spain, December 2011


• M. Salzmann and R. Urtasun
  Physically-based Motion Models for 3D Tracking: A Convex Formulation
  In International Conference on Computer Vision (ICCV), Barcelona, Spain, November 2011


• T. Hazan and R. Urtasun
  Approximated Structured Prediction for Learning Large Scale Graphical Models
  Arxiv 1006.2899, June 2010


• J. Peng, T. Hazan, D. McAllester and R. Urtasun
  Convex Max-Product over Compact Sets for Protein Folding  (oral)
  In International Conference in Machine Learning (ICML), Bellevue, Washington, June 2011


• A. Geiger, M. Lauer and R. Urtasun
  A generative model for 3D urban scene understanding from movable platforms [pdf] [talk] [slides] [data] [software]  (oral)
  In Conference of Computer Vision and Pattern Recognition (CVPR), Colorado Springs, June 2011


• A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
  Distributed Message Passing for Large Scale Graphical Models [pdf] [software]
  In Conference of Computer Vision and Pattern Recognition (CVPR), Colorado Springs, June 2011


• A. Shyr, T. Darrell, M. Jordan and R. Urtasun
  Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation
  In Conference of Computer Vision and Pattern Recognition (CVPR), Colorado Springs, June 2011


• H. Hamer, J. Gall, R. Urtasun and L. Van Gool
  Data-Driven Animation of Hand- Object Interaction  (oral)
  In Face and Gesture Recognition (FGR), Santa Barbara, April 2011

2010

• A. Kapoor, K. Grauman, R. Urtasun and T. Darrell.
  Gaussian Processes for Object Categorization
  In International Journal in Computer Vision, (IJCV) 2010


• T. Hazan and R. Urtasun
  A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction
  To appear in Neural Information Processing Systems (NIPS), Vancouver, December 2010


• M. Salzmann and R. Urtasun
  Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation
  To appear in Neural Information Processing Systems (NIPS), Vancouver, December 2010


• T. Kim, G. Shakhnarovich and R. Urtasun
  Sparse coding for learning interpretable spatio-temporal primitives
  To appear in Neural Information Processing Systems (NIPS), Vancouver, December 2010


• A. Geiger, M. Roser and R. Urtasun
  Efficient Large-Scale Stereo Matching [pdf] [talk] [software]  (oral)
  In Asian Conference in Computer Vision (ACCV), Queenstown, New Zealand, November 2010


• C. M. Christoudias, R. Urtasun, M. Salzmann and T. Darrell
  Learning to Recognize Objects from Unseen Modalities [pdf] [project page][software]
  In European Conference in Computer Vision (ECCV), Crete, September 2010


• M. Salzmann and R. Urtasun
  Combining Discriminative and Generative Methods for 3D Deformable Surface and Articulated Pose Reconstruction [pdf] [supplementary]  (oral)
  In Conference in Computer Vision and Pattern Recognition (CVPR), San Francisco, June 2010


• A. Shyr, R. Urtasun and M. I. Jordan
  Sufficient Dimensionality Reduction for Visual Sequence Classification
  In Conference in Computer Vision and Pattern Recognition (CVPR), San Francisco, June 2010


• M. Salzmann, C. Ek, R. Urtasun and T. Darrell
  Factorized Orthogonal Latent Spaces
  In International Conference on Artificial Intelligence and Statistics (AISTATS), Sardinia, Italy, May 2010


• M. Salzmann, C. H. Ek, R. Urtasun and T. Darrell
  FOLS: Factorized Orthogonal Latent Spaces.
  In Learning Workshop (Snowbird) Snowbird, Utah, April 2010
  


• M. Salzmann and R. Urtasun
  A Constrained Combination of Discriminative and Generative Methods.
  In Learning Workshop (Snowbird) Snowbird, Utah, April 2010
  

2009

• N. D. Lawrence and R. Urtasun
  Non-linear Matrix Factorization with Gaussian Processes [pdf] [software]  (oral)
  In International Conference in Machine Learning (ICML), Montreal June 2009


• A. Geiger, R. Urtasun and T. Darrell
  Rank Priors for Continuous Non-Linear Dimensionality Reduction [pdf] [video]
  In Conference in Computer Vision and Pattern Recognition (CVPR), Miami June 2009


• C. M. Christoudias, R. Urtasun, A. Kapoor and T. Darrell
  Co-training with noisy perceptual observations
  In Conference in Computer Vision and Pattern Recognition (CVPR), Miami June 2009


• C. M. Christoudias, R. Urtasun and T. Darrell
  Bayesian Localized Multiple Kernel Learning.
  In Learning from Multiple Sources with Applications to Robotics Workshop at NIPS, Whister, Canada, December 2009
  


• R. Urtasun
  Non-Parametric Latent Variable Models for Shape and Motion Analysis.
  Invited talk in MIRAGE Versailles, France, May 2009
  


• N. D. Lawrence and R. Urtasun
  Non-Linear Matrix Factorization.
  In Learning Workshop (Snowbird) Clearwater, Florida, April 2009
  


• R. Urtasun, A. Geiger and T. Darrell
  Rank Priors for Continuous Non-Linear Dimensionality Reduction.
  In Learning Workshop (Snowbird) Clearwater, Florida, April 2009
  


• C. M. Christoudias, R. Urtasun, A. Kapoor and T. Darrell
  Co-training with Noisy Perceptual Observations.
  In Learning Workshop (Snowbird) Clearwater, Florida, April 2009
  

2008

• C. M. Christoudias, R. Urtasun and T. Darrell
  Multi-View Learning in the Presence of View Disagreement [pdf] [talk]  (oral)
  In Conference on Uncertainty in Artificial Intelligence (UAI) Helsinki, Finland, July 2008


• R. Urtasun, D. J. Fleet, A. Geiger, J. Popovic, T. Darrell and N. D. Lawrence.
  Topologically-Constrained Latent Variable Models. [pdf] [video] [talk]  (oral)
  In International Conference in Machine Learning (ICML) Helsinki, Finland, July 2008


• R. Urtasun and T. Darrell
  Local Probabilistic Regression for Activity-Independent Human Pose Inference
  In Conference in Computer Vision and Pattern Recognition (CVPR) Anchorage, Alaska, June 2008


• M. Salzmann, R. Urtasun and P. Fua
  Local Deformation Models for Monocular 3D Shape Recovery  (oral)
  In Conference in Computer Vision and Pattern Recognition (CVPR) Anchorage, Alaska, June 2008


• C. M. Christoudias, R. Urtasun and T. Darrell
  Unsupervised Distributed Feature Selection for Multi-view Object Recognition
  In Conference in Computer Vision and Pattern Recognition (CVPR) Anchorage, Alaska, June 2008


• R. Urtasun and T. Darrell
  Local Probabilistic Regression for Activity-Independent Human Pose Inference.
  In Learning Workshop (Snowbird) Snowbird, Utah, April 2008
  


• R. Urtasun, A. Quattoni, N. D. Lawrence and T. Darrell
  Transfering Nonlinear Representations using Gaussian Processes with a Shared Latent Space.
  In Learning Workshop (Snowbird) Snowbird, Utah, April 2008
  


• R. Urtasun, A. Quattoni, N. Lawrence and T. Darrell
  Transferring Nonlinear Representations using Gaussian Processes with a Shared Latent Space
  MIT technical report, 2008

2007

• A. Kapoor, K. Grauman, R. Urtasun and T. Darrell
  Active Learning with Gaussian Processes for Object Categorization
  In International Conference in Computer Vision (ICCV) Rio de Janeiro, October 2007


• R. Urtasun and T. Darrell
  Discriminative Gaussian Process Latent Variable Models for Classification (oral)
  International Conference in Machine Learning (ICML) Oregon, June 2007


• R. Urtasun, D. J. Fleet and N. D. Lawrence
  Modeling human locomotion with topologically constrained latent variable models.
  In ICCV Workshop on Human Motion: Understanding, Modeling, Capture and Animation, Rio de Janeiro, Brazil, October 2007
  

2006

• R. Urtasun.
  Motion Models for Robust 3D Human Body Tracking
  Phd Thesis 3541, EPFL 2006
  
• R. Urtasun, D. J. Fleet and P. Fua.
  Temporal Motion Models for Monocular and Multiview 3D Human Body Tracking
  In Computer Vision and Image Understanding special issue Modeling People, (CVIU) 2006


• R. Urtasun, D. J.Fleet and P. Fua.
  Gaussian Process Dynamical Models for 3D people tracking. [pdf] [video_tracking] [video_model]
  In Conference on Computer Vision and Pattern Recognition (CVPR) New York, June 2006


• R. Urtasun, D. J. Fleet, A. Hertzmann and P. Fua
  Gaussian Processes for Monocular 3D People tracking.
  In Gaussian Processes in Practice Workshop Bletchley Park, U.K, June 2006
  

2005

• L. Herda, R. Urtasun and P. Fua.
  Hierarchical Implicit Surface Joint Limits for Human Body Tracking.
  In Computer Vision and Image Understanding, (CVIU) 2005


• R. Urtasun, D. J.Fleet, A. Hertzmann and P. Fua.
  Priors for People Tracking from Small Training Sets. [pdf] [video_tracking]  (oral)
  In International Conference in Computer Vision (ICCV) Beijing, China, October 2005


• R. Urtasun, D. J.Fleet and P. Fua.
  Monocular 3D Tracking of the Golf Swing.
  In Conference on Computer Vision and Pattern Recognition (CVPR) San Diego, CA, June 2005

2004

• R. Urtasun, P. Glardon, R. Boulic, D. Thalmann and P. Fua.
  Style-based Motion Synthesis. [pdf] [video]
  In Computer Graphics Forum (CGF), Vol. 23, number 4 pp 799-812. December 2004


• R. Urtasun, P. Fua.
  3D Human Body Tracking using Deterministic Motion Models.
  In European Conference on Computer Vision (ECCV), Prague, Czech Republic, May 2004


• L.Herda, R. Urtasun, P. Fua.
  Hierarchical Implicit Surface Joint Limits to Constrain Video-Based Motion Capture.
  In European Conference on Computer Vision (ECCV), Prague, Czech Republic, May 2004


• R. Urtasun, P. Fua.
  3D Tracking for Gait Characterization and Recognition.  (oral)
  In Proceeding of the 6th International Conference on Automatic Face and Gesture Recognition (FGR), Seoul, Korea, May 2004. IEEE Computer Society.


• R. Urtasun M. Salzmann and P. Fua
  3D Morphing without User Interaction
  EPFL technical report, 2004

2003

• L.Herda, R.Urtasun, P.Fua, A.Hanson.
  Automatic Determination of Shoulder Joint Limits using Quaternion Field Boundaries.
  International Journal of Robotics Research (IJRR), 22(6): 419 - 436, 2003.


• P. Dokladal, I. Bloch, M. Couprie, D. Ruijters, R. Urtasun and L. Garnero.
  Topologically Controlled Segmentation of 3D Magnetic Resonance Images of the Head by using Morphological Operators.
  Pattern Recognition, 36(10):2463 - 2478, 2003.

2002

• L.Herda, R.Urtasun, P.Fua and A.Hanson.
  An Automatic Method for Determining Quaternion Field Boundaries for Ball-and-Socket Joint Limits.
  In Proceedings of the 5th International Conference on Automatic Face and Gesture Recognition (FGR), pages 95 - 100, Washington DC, May 2002. IEEE Computer Society.

2001

• P. Dokladal, R. Urtasun, I. Bloch and L. Garnero.
  Segmentation of 3D head MR images using Morphological reconstruction under constraints and automatic selection of markers.
  In International Conference on Image Processing (ICIP), pages 1075-1078, Thessaloniki, Greece, October 2001
  

2000

• R. Urtasun
  Automatic segmentation of a fix number of markers (apply to the cerebellum and brainstem)
  Telecom Paris technical report, 2000


• R. Urtasun
  Segmentation of a Guinea pig using mathematical morphology
  Telecom Paris technical report, 2000


• R. Urtasun
  Implementation of a tool to Visualize Protocol Design and Processing
  Eurecom's technical report, 2000