Cross-Modal Deep Variational Hashing In this paper, we propose a cross-modal deep variational hashing (CMDVH) method for cross-modality multimedia retrieval. Unlike existing cross-modal hashing methods which learn a single pair of projections to map each example as a binary... VE Liong,J Lu,...
This paper presents a novel cross-modal retrieval framework, called deep dual variational hashing (DDVH), by exploring dual variational mappings between modalities to bridge the inherent modality gap. Specifically, DDVH consists of two sub-modules, which are visual variational mapping (VVM) and ...
Recently, researchers leverage Deep Neural Network (DNN) to learn nonlinear transformations for each modality to obtain transformed features in a common subspace where cross-modal matching can be performed. However, the statistical characteristics of the original features for each modality are not ...