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|Title:||End-to-End Learning of Deformable Mixture of Parts and Deep Convolutional Neural Networks for Human Pose Estimation|
|Publisher:||(IEEE) Institute of Electrical and Electronics Engineers|
|Citation:||End-to-End Learning of Deformable Mixture of Parts and Deep Convolutional Neural Networks for Human Pose Estimation, Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol.N/A, 2016, pp. 3073-3082|
|Disclaimer:||This work has been made available to the staff and students of the University of Sydney for the purposes of research and study only. It constitutes material that is held by the University for the purposes of reporting for HERDC and the ERA. This work may not be downloaded, copied and distributed to any third party .|
|Type:||E1 - Conference proceedings EXT|
|Appears in Collections:||University of Sydney Research Outputs|
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