暂无分享,去创建一个
[1] Luc Van Gool,et al. Dynamic 3D Scene Analysis from a Moving Vehicle , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[2] Daphne Koller,et al. Learning Spatial Context: Using Stuff to Find Things , 2008, ECCV.
[3] David A. McAllester,et al. A discriminatively trained, multiscale, deformable part model , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[4] Martial Hebert,et al. Onboard contextual classification of 3-D point clouds with learned high-order Markov Random Fields , 2009, 2009 IEEE International Conference on Robotics and Automation.
[5] Nico Blodow,et al. Towards 3D Point cloud based object maps for household environments , 2008, Robotics Auton. Syst..
[6] Alexei A. Efros,et al. Putting Objects in Perspective , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[7] Vladimir Kolmogorov,et al. Optimizing Binary MRFs via Extended Roof Duality , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[8] Dieter Fox,et al. Sparse distance learning for object recognition combining RGB and depth information , 2011, 2011 IEEE International Conference on Robotics and Automation.
[9] Ben Taskar,et al. Discriminative learning of Markov random fields for segmentation of 3D scan data , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[10] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[11] Vladimir G. Kim,et al. Shape-based recognition of 3D point clouds in urban environments , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[12] Antonio Torralba,et al. Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes , 2003, NIPS.
[13] Siddhartha S. Srinivasa,et al. Structure discovery in multi-modal data: A region-based approach , 2011, 2011 IEEE International Conference on Robotics and Automation.
[14] Martial Hebert,et al. 3-D scene analysis via sequenced predictions over points and regions , 2011, 2011 IEEE International Conference on Robotics and Automation.
[15] O. Barinova,et al. NON-ASSOCIATIVE MARKOV NETWORKS FOR 3D POINT CLOUD CLASSIFICATION , 2010 .
[16] Quoc V. Le,et al. High-accuracy 3D sensing for mobile manipulation: Improving object detection and door opening , 2009, 2009 IEEE International Conference on Robotics and Automation.
[17] Pierre Hansen,et al. Roof duality, complementation and persistency in quadratic 0–1 optimization , 1984, Math. Program..
[18] Yun Jiang,et al. Learning to place new objects , 2011, 2012 IEEE International Conference on Robotics and Automation.
[19] Thorsten Joachims,et al. Training structural SVMs when exact inference is intractable , 2008, ICML '08.
[20] Ben Taskar,et al. Learning associative Markov networks , 2004, ICML.
[21] Takeo Kanade,et al. Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces , 2010, NIPS.
[22] Ashutosh Saxena,et al. Efficient grasping from RGBD images: Learning using a new rectangle representation , 2011, 2011 IEEE International Conference on Robotics and Automation.
[23] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[24] Andrew Y. Ng,et al. Integrating Visual and Range Data for Robotic Object Detection , 2008, ECCV 2008.
[25] Tsuhan Chen,et al. Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models , 2010, NIPS.
[26] Ashutosh Saxena,et al. Learning Depth from Single Monocular Images , 2005, NIPS.
[27] Antonio Torralba,et al. Contextual Priming for Object Detection , 2003, International Journal of Computer Vision.
[28] Thomas Hofmann,et al. Support vector machine learning for interdependent and structured output spaces , 2004, ICML.
[29] Thorsten Joachims,et al. Cutting-plane training of structural SVMs , 2009, Machine Learning.
[30] Dieter Fox,et al. A large-scale hierarchical multi-view RGB-D object dataset , 2011, 2011 IEEE International Conference on Robotics and Automation.
[31] Daniel Huber,et al. Using Context to Create Semantic 3D Models of Indoor Environments , 2010, BMVC.