Cycle-Consistent Deep Generative Hashing for Cross-Modal Retrieval.
IEEE Transactions on Image Processing(2019)
摘要
In this paper, we propose a novel deep generative approach to cross-modal retrieval to learn hash functions in the absence of paired training samples through the cycle consistency loss. Our proposed approach employs adversarial training scheme to learn a couple of hash functions enabling translation between modalities while assuming the underlying semantic relationship. To induce the hash codes wi...
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关键词
Semantics,Binary codes,Training,Correlation,Gallium nitride,Data models
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