In recent years, cross-modal retrieval has drawn much attention due to the rapid growth of
multimodal data. It takes one type of data as the query to retrieve relevant data of another …

With the development of web technology, multi-modal or multi-view data has surged as a
major stream for big data, where each modal/view encodes individual property of data …

Multimodal hashing methods have gained considerable attention in recent years due to their
effectiveness and efficiency for cross-modal similarity searches. Existing multimodal hashing …

As the rapid development of deep neural networks, multi-modal learning techniques are
widely concerned. Cross-modal retrieval is an important branch of multimodal learning. Its …

The purpose of cross-modal retrieval is to find the relationship between different modal
samples and to retrieve other modal samples with similar semantics by using a certain …

To improve the security, robustness and imperceptibility of watermark schemes, a novel
watermark scheme is devised by fusing multiple watermark techniques, including lifting …

Cross-modal retrieval aims to retrieve data in one modality by a query in another modality,
which has been a very interesting research issue in the field of multimedia, information …

Cross-modal audio–visual correlation learning has been an interesting research topic,
which aims to capture and understand semantic correspondences between audio and …

The problem of cross-modal retrieval has attracted significant attention in the cross-media
retrieval community. One key challenge of cross-modal retrieval is to eliminate the …

Cross-modal retrieval has become a hot issue in past years. Many existing works pay
attentions on correlation learning to generate a common subspace for cross-modal …