From zero-shot learning to conventional supervised classification: Unseen visual data synthesis

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

Volumn 2017-January, Issue , 2017, Pages 6165-6174

  Long, Yang ^a   Liu, Li ^b   Shao, Ling ^b   Shen, Fumin ^c   Ding, Guiguang ^d   Han, Jungong ^e  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b UNIVERSITY OF EAST ANGLIA   (United Kingdom)

^c UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^d TSINGHUA UNIVERSITY   (China)

^e NORTHUMBRIA UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; OBJECT RECOGNITION; SEMANTICS;

BENCHMARK DATASETS; EXTRACTION MECHANISMS; REALISTIC APPLICATIONS; ROBUST OBJECT RECOGNITION; SEMANTIC ATTRIBUTE; STATE OF THE ART; SUPERVISED CLASSIFICATION; VISUAL FEATURE;

COMPUTER VISION;

EID: 85041913771     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.653     Document Type: Conference Paper

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