Hashing has been widely investigated for large-scale image retrieval due to its search
effectiveness and computation efficiency. In this work, we propose a novel Semantic Guided …

The focus of this survey is on the analysis of two modalities of multimodal deep learning:
image and text. Unlike classic reviews of deep learning where monomodal image classifiers …

Supervised cross-modal hashing has attracted much attention. However, there are still some
challenges, eg, how to effectively embed the label information into binary codes, how to …

With 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 …

In recent years, Cross-Modal Hashing (CMH) has attracted much attention due to its fast
query speed and efficient storage. Previous studies have achieved promising results for …

Due to the continuous growth of large-scale multi-modal data and increasing requirements
for retrieval speed, deep cross-modal hashing has gained increasing attention recently …

Recently, supervised cross-modal hashing has attracted much attention and achieved
promising performance. To learn hash functions and binary codes, most methods globally …

Cross-modal hashing, favored for its effectiveness and efficiency, has received wide
attention to facilitating efficient retrieval across different modalities. Nevertheless, most …

In recent years, many achievements have been made in improving the performance of
supervised cross-modal hashing. However, it remains an open issue on how to fully explore …

Compact hash codes can facilitate large-scale multimedia retrieval, significantly reducing
storage and computation. Most hashing methods learn hash functions based on the data …