A deep regression architecture with two-stage re-initialization for high performance facial landmark detection

Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

Volumn 2017-January, Issue , 2017, Pages 3691-3700

  Lv, Jiangjing ^a,b   Shao, Xiaohu ^a,b   Xing, Junliang ^c   Cheng, Cheng ^a   Zhou, Xi ^a  

^a University of Chinese Academy of Sciences   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; IMAGE ENHANCEMENT; NETWORK ARCHITECTURE; PATTERN RECOGNITION; REGRESSION ANALYSIS;

COMPETING ALGORITHMS; DEEP ARCHITECTURES; FACIAL LANDMARK DETECTION; IMPROVE PERFORMANCE; INITIAL ESTIMATION; INITIALIZATION PROBLEM; MAPPING FUNCTIONS; REGRESSION FUNCTION;

FACE RECOGNITION;

EID: 85030213048     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.393     Document Type: Conference Paper

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