Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation-Reference-Cited by-同舟云学术

Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation

Published:2016-10-01 Issue:1 Volume:122 Page:149-168
ISSN:0920-5691
Container-title:International Journal of Computer Vision
language:en
Short-container-title:Int J Comput Vis

Author:

Li Sijin^ORCID,Zhang Weichen,Chan Antoni B.^ORCID

Funder

City University of Hong Kong (HK)

Research Grants Council of the Hong Kong Special Administrative Region, China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s11263-016-0962-x.pdf

Reference44 articles.

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3. Bastien, F., Lamblin, P., Pascanu, R., Bergstra, J., Goodfellow, I. J., Bergeron, A., Bouchard, N., & Bengio, Y. (2012). Theano: new features and speed improvements. In NIPS: Deep learning and unsupervised feature learning workshop

4. Bengio, Y., Mesnil, G., Dauphin, Y., & Rifai, S. (2013). Better mixing via deep representations. In ICML (pp. 552–560).

5. Bregler, C., Malik, J., & Pullen, K. (2004). Twist based acquisition and tracking of animal and human kinematics. International Journal of Computer Vision, 56(3), 179–194.

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