Keep it SMPL: Automatic estimation of 3D human pose and shape from a single image

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9909 LNCS, Issue , 2016, Pages 561-578

  Bogo, Federica ^b   Kanazawa, Angjoo ^c   Lassner, Christoph ^a,d   Gehler, Peter ^a,d   Romero, Javier ^a   Black, Michael J ^a  

^a MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS   (Germany)

^b MICROSOFT RESEARCH   (United Kingdom)

^c UNIVERSITY OF MARYLAND   (United States)

^d UNIVERSITY OF TÜBINGEN   (Germany)

Author keywords

2D to 3D; 3D body shape; CNN; Human pose

Indexed keywords

HOSIERY MANUFACTURE; POPULATION STATISTICS;

2D-TO-3D; AMOUNT OF INFORMATION; AUTOMATIC ESTIMATION; BODY SHAPES; HUMAN POSE; JOINT LOCATIONS; OBJECTIVE FUNCTIONS; STATE OF THE ART;

3D MODELING;

EID: 84990053222     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-46454-1_34     Document Type: Conference Paper

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