Towards computational baby learning: A weakly-supervised approach for object detection

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 999-1007

  Liang, Xiaodan ^a,b   Liu, Si ^a,d   Wei, Yunchao ^a,c   Liu, Luoqi ^a   Lin, Liang ^b   Yan, Shuicheng ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b SUN YAT SEN UNIVERSITY   (China)

^c BEIJING JIAOTONG UNIVERSITY   (China)

^d University of Chinese Academy of Sciences   (China)

Author keywords

[No Author keywords available]

Indexed keywords

KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; OBJECT DETECTION; OBJECT RECOGNITION;

COMPUTATIONAL MODEL; CONVOLUTIONAL NEURAL NETWORK; EXEMPLAR LEARNING; OBJECT CATEGORIES; POSITIVE INSTANCES; PRIOR KNOWLEDGE; STATE OF THE ART; TRACKING SOLUTIONS;

COMPUTER VISION;

EID: 84973882796     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.120     Document Type: Conference Paper

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