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Daniel Munoz
Daniel Munoz
Machine Learning R&D
Verified email at cs.cmu.edu - Homepage
Title
Cited by
Cited by
Year
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
4222009
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
3522014
Stacked hierarchical labeling
D Munoz, JA Bagnell, M Hebert
Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010
2822010
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
1652011
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
1552009
Learning message-passing inference machines for structured prediction
S Ross, D Munoz, M Hebert, JA Bagnell
CVPR 2011, 2737-2744, 2011
1522011
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
1382008
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
822013
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
752013
Co-inference for multi-modal scene analysis
D Munoz, JA Bagnell, M Hebert
Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012
732012
Inference Machines Parsing Scenes via Iterated Predictions
D Munoz
Carnegie Mellon University, 2013
252013
Speedmachines: Anytime structured prediction
A Grubb, D Munoz, JA Bagnell, M Hebert
arXiv preprint arXiv:1312.0579, 2013
92013
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
42010
Learning Deep Inference Machines
JA Bagnell, A Grubb, D Munoz, S Ross
The Learning Workshop, 2010
22010
automatic 3d point cloud classification of urban environments
D Munoz, N Vandapel, M Hebert
Security, 2007
22007
Semantic perception, mapping and exploration
A Nüchter, RB Rusu, D Holz, D Munoz
Robotics and Autonomous Systems 62 (5), 617-618, 2014
12014
Using Inference Machines for Perception Tasks
D Munoz, D Bagnell, M Hebert
2013
Advances in Minimizing Submodular Energy Functions with Graph Cuts
D Munoz
2008
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