Cross-modal hashing (CMH) has gained much attention due to its effectiveness and
efficiency in facilitating efficient retrieval between different modalities. Whereas, most …

Cross-modal hashing~(CMH) is an efficient technique to retrieve relevant data across
different modalities, such as images, texts, and videos, which has attracted more and more …

Owing to its query and storage efficiency, hash learning has sparked much interest for Cross-
Modal Retrieval (CMR) task. Previous literatures have proved the superiority of supervised …

Deep hashing has attracted broad interest in cross-modal retrieval because of its low cost
and efficient retrieval benefits. To capture the semantic information of raw samples and …

With the dramatic increase in the amount of multimedia data, cross-modal similarity retrieval
has become one of the most popular yet challenging problems. Hashing offers a promising …

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 …

Deep hashing has been widely used for large-scale cross-modal retrieval benefited from the
low storage cost and fast search speed. However, most existing deep supervised methods …

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 …

Recently, deep hashing-based cross-modal retrieval has attracted much attention of
researchers, due to its advantages of fast retrieval efficiency and low storage overhead, etc …

Cross-modal hashing (CMH) has attracted considerable attention in recent years. Almost all
existing CMH methods primarily focus on reducing the modality gap and semantic gap, ie …