Cross-Modal Self-Taught Hashing for large-scale image retrieval
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- 作者：Liang Xiea ; whutxl@hotmail.com" class="auth_mail" title="E-mail the corresponding author ; Lei Zhub ; leizhu0608@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Peng Panc ; panpeng@mail.hust.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Yansheng Luc ; lys@mail.hust.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Image retreival ; Cross-modal hashing ; Self-taught learning ; Semantic correlation
- 刊名：Signal Processing
- 出版年：2016
- 出版时间：July 2016
- 年：2016
- 卷：124
- 期：Complete
- 页码：81-92
- 全文大小：557 K
文摘
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Self-Taught Scheme is used for large scale cross-modal image retrieval.
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Hierarchical Multi-Modal Topic Learning is proposed to learn semantic topics.
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Robust Matrix Factorization is used to transfer topics to hash codes.
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Our method can be easily extended without any changes in the whole framework.