| Contextual classification with functional max-margin markov networks D Munoz, JA Bagnell, N Vandapel, M Hebert 2009 IEEE Conference on Computer Vision and Pattern Recognition, 975-982, 2009 | 442 | 2009 |
| Pose machines: Articulated pose estimation via inference machines V Ramakrishna, D Munoz, M Hebert, J Andrew Bagnell, Y Sheikh Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 367 | 2014 |
| Stacked hierarchical labeling D Munoz, JA Bagnell, M Hebert Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010 | 286 | 2010 |
| 3-D scene analysis via sequenced predictions over points and regions X Xiong, D Munoz, JA Bagnell, M Hebert 2011 IEEE International Conference on Robotics and Automation, 2609-2616, 2011 | 165 | 2011 |
| Onboard contextual classification of 3-d point clouds with learned high-order markov random fields D Munoz, N Vandapel, M Hebert 2009 IEEE International Conference on Robotics and Automation, 2009 | 159 | 2009 |
| Learning message-passing inference machines for structured prediction S Ross, D Munoz, M Hebert, JA Bagnell CVPR 2011, 2737-2744, 2011 | 152 | 2011 |
| Directional associative markov network for 3-d point cloud classification D Munoz, N Vandapel, M Hebert 3D Data Processing, Visualization and Transmission (3DPVT), Fourth …, 2008 | 140 | 2008 |
| Efficient temporal consistency for streaming video scene analysis O Miksik, D Munoz, JA Bagnell, M Hebert 2013 IEEE International Conference on Robotics and Automation, 133-139, 2013 | 85 | 2013 |
| Efficient 3-d scene analysis from streaming data H Hu, D Munoz, JA Bagnell, M Hebert 2013 IEEE international conference on robotics and automation, 2297-2304, 2013 | 77 | 2013 |
| Co-inference for multi-modal scene analysis D Munoz, JA Bagnell, M Hebert Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 74 | 2012 |
| Inference Machines Parsing Scenes via Iterated Predictions D Munoz Carnegie Mellon University, 2013 | 25 | 2013 |
| Speedmachines: Anytime structured prediction A Grubb, D Munoz, JA Bagnell, M Hebert arXiv preprint arXiv:1312.0579, 2013 | 9 | 2013 |
| An architecture for online semantic labeling on UGVs A Suppé, L Navarro-Serment, D Munoz, D Bagnell, M Hebert Unmanned Systems Technology XV 8741, 252-257, 2013 | 4* | 2013 |
| On two methods for semi-supervised structured prediction D Munoz, JA Bagnell, M Hebert Robotics Institute, Carnegie Mellon University, 2010 | 4 | 2010 |
| Semantic perception, mapping and exploration A Nüchter, RB Rusu, D Holz, D Munoz Robotics and Autonomous Systems 62 (5), 617-618, 2014 | 2 | 2014 |
| Learning Deep Inference Machines JA Bagnell, A Grubb, D Munoz, S Ross The Learning Workshop, 2010 | 2 | 2010 |
| Using Inference Machines for Perception Tasks D Munoz, D Bagnell, M Hebert | | 2013 |
martial hebertCMUVerified email at ri.cmu.edu
