Cross-modal retrievalDiscrete optimizationOnline hashingLearning to hashWith the prevalence of multimedia content on the Web which usually continuously comes in a stream fashion, online cross-modal hashing methods have attracted extensive interest in recent years. However, most online hashing methods adopt...
Discrete online cross-modal hashing作者: Highlights: • Different from the majority of related methods, DOCH is a discrete one. • By keeping the binary constraints, quantization error can be avoided. • By preserving the similarity in Hamming space, DOCH learns accurate hash codes. • ...
Recently, cross-modal hashing (CMH) methods have attracted much attention. Many methods have been explored; however, there are still some issues that need to be further considered. 1) How to efficiently construct the correlations among heterogeneous modalities. 2) How to solve the NP-hard optimi...
into two separate stages or treat the discrete optimization problem simplistically as a continuous one, which leads tosuboptimal results. Recently, a few discrete multi-modal hashing methods that try to address such issues have emerged, but they stillignore several important discrete constraints (such ...
Deep optimization class. Based on an array ofMCBiteOpt objects. This "deep" method pushes the newly-obtained solution to the random CBiteOpt object which is then optimized. This method, while increasing the convergence time, is able to solve complex multi-modal functions. ...
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Cross-Modal Discrete HashingLiongVeniceErinLuJiwenTanYap-PengingentaconnectPattern Recognition
Supervised cross-modal hashing has attracted many researchers. In these studies, they seek a common semantic space or directly regress the zero-one label information into the Hamming space. Although they achieve many achievements, they neglect some issues: 1) some methods of the classification task...
Cross-modalDiscrete optimizationIn this paper, we present a new cross-modal discrete hashing (CMDH) approach to learn compact binary codes for cross-modal multimedia search. Unlike most existing cross-modal hashing methods which usually relax the optimization objective function to obtain hash codes, ...
Kernel discriminant analysisCross-modal hashing methods have drawn considerable attention due to the rapid growth of multi-modal data. To obtain efficient binary codes in a low-dimensional Hamming space, most existing approaches relaxed the discrete constraint, which could cause quantization loss and ...