Handbook of combinatorics (vol. 1)
Handbook of combinatorics (vol. 1)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cascaded models for articulated pose estimation
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Improved human parsing with a full relational model
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Recovering human body configurations: combining segmentation and recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Efficient inference with multiple heterogeneous part detectors for human pose estimation
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Fast multi-aspect 2D human detection
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Parsing human motion with stretchable models
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Learning effective human pose estimation from inaccurate annotation
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Articulated people detection and pose estimation: Reshaping the future
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
N-best maximal decoders for part models
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Articulated part-based model for joint object detection and pose estimation
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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While human pose estimation (HPE) techniques usually process each test image independently, in real applications images come in collections containing interdependent images. Often several images have similar backgrounds or show persons wearing similar clothing (foreground). We present a novel human pose estimation technique to exploit these dependencies by sharing appearance models between images. Our technique automatically determines which images in the collection should share appearance. We extend the state-of-the art HPE model of Yang and Ramanan to include our novel appearance sharing cues and demonstrate on the highly challenging Leeds Sports Poses dataset that they lead to better results than traditional single-image pose estimation.