Cross-modal hashing has garnered considerable attention and gained great success in
many cross-media similarity search applications due to its prominent computational …

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 …

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 …

Recently, numerous unsupervised cross-modal hashing methods have been proposed to
deal the image-text retrieval tasks for the unlabeled cross-modal data. However, when these …

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 …

Hashing methods have captured much attention for cross-modal retrieval in recent years.
Most existing approaches mainly focus on preserving the semantic similarity across …

The amount of multi-modal data available on the Internet is enormous. Cross-modal hash
retrieval maps heterogeneous cross-modal data into a single Hamming space to offer fast …

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 …

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 …