A self-paced multiple-instance learning framework for co-saliency detection

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 594-602

  Zhang, Dingwen ^a   Meng, Deyu ^b   Li, Chao ^a   Jiang, Lu ^c   Zhao, Qian ^b   Han, Junwei ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

^c Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DATA MINING;

BENCHMARK DATASETS; BIOLOGICAL MECHANISMS; GENERALIZATION CAPABILITY; METRIC MEASUREMENT; MULTIPLE-INSTANCE LEARNING; REAL APPLICATIONS; RELIABILITY AND STABILITY; SELF-PACED LEARNING;

LEARNING SYSTEMS;

EID: 84973896942     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.75     Document Type: Conference Paper

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