Object Detection by 3D Aspectlets and Occlusion Reasoning
暂无分享,去创建一个
[1] Daphne Koller,et al. A segmentation-aware object detection model with occlusion handling , 2011, CVPR 2011.
[2] Silvio Savarese,et al. Understanding Indoor Scenes Using 3D Geometric Phrases , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[3] P. Green. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination , 1995 .
[4] David A. Forsyth,et al. Thinking Inside the Box: Using Appearance Models and Context Based on Room Geometry , 2010, ECCV.
[5] Konrad Schindler,et al. Explicit Occlusion Modeling for 3D Object Class Representations , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[6] Silvio Savarese,et al. Estimating the aspect layout of object categories , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[7] Silvio Savarese,et al. Toward coherent object detection and scene layout understanding , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[8] Jamie Shotton,et al. The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[9] Peter V. Gehler,et al. Occlusion Patterns for Object Class Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[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] David A. McAllester,et al. Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[12] Antonio Torralba,et al. LabelMe: A Database and Web-Based Tool for Image Annotation , 2008, International Journal of Computer Vision.
[13] Charless C. Fowlkes,et al. Discriminative Models for Multi-Class Object Layout , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[14] Luc Van Gool,et al. The 2005 PASCAL Visual Object Classes Challenge , 2005, MLCW.
[15] David G. Lowe,et al. Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[16] A. Torralba,et al. The role of context in object recognition , 2007, Trends in Cognitive Sciences.
[17] Bernt Schiele,et al. Monocular 3D scene understanding with explicit occlusion reasoning , 2011, CVPR 2011.
[18] Alexei A. Efros,et al. Putting Objects in Perspective , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[19] Silvio Savarese,et al. 3D generic object categorization, localization and pose estimation , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[20] Thomas Hofmann,et al. Support vector machine learning for interdependent and structured output spaces , 2004, ICML.
[21] Ramakant Nevatia,et al. Detection of multiple, partially occluded humans in a single image by Bayesian combination of edgelet part detectors , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[22] Jitendra Malik,et al. Poselets: Body part detectors trained using 3D human pose annotations , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[23] Shuicheng Yan,et al. An HOG-LBP human detector with partial occlusion handling , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[24] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[25] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.
[26] Alexei A. Efros,et al. Recovering Occlusion Boundaries from a Single Image , 2007, 2007 IEEE 11th International Conference on Computer Vision.