Maximum-margin structured learning with deep networks for 3D human pose estimation

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 2848-2856

  Li, Sijin ^a   Zhang, Weichen ^a   Chan, Antoni B ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; COST FUNCTIONS; FEATURE EXTRACTION; GESTURE RECOGNITION; NEURAL NETWORKS; STATISTICAL TESTS; VECTOR SPACES;

3D HUMAN POSE ESTIMATION; CONVOLUTIONAL NEURAL NETWORK; DEEP NEURAL NETWORKS; IMAGE FEATURE EXTRACTIONS; NETWORK STRUCTURES; STATE OF THE ART; STRUCTURED LEARNING; STRUCTURED SUPPORTS;

MOTION ESTIMATION;

EID: 84973861613     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.326     Document Type: Conference Paper

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