Cross-modal retrieval has become a highlighted research topic for retrieval across
multimedia data such as image and text. A two-stage learning framework is widely adopted …

Cross-modal retrieval has drawn wide interest for retrieval across different modalities (such
as text, image, video, audio, and 3-D model). However, existing methods based on a deep …

Cross-modal retrieval aims to realize accurate and flexible retrieval across different
modalities of data, eg, image and text, which has achieved significant progress in recent …

Cross-modal retrieval aims to enable flexible retrieval across different modalities. The core
of cross-modal retrieval is how to measure the content similarity between different types of …

The problem of cross-modal retrieval, eg, using a text query to search for images and vice-
versa, is considered in this paper. A novel model involving correspondence autoencoder …

Cross-modal retrieval emphasizes understanding inter-modality semantic correlations,
which is often achieved by designing a similarity function. Generally, one of the most …

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 retrieval takes one type of data as the query to retrieve relevant data of another
type. Most of existing cross-modal retrieval approaches were proposed to learn a common …

Cross-modal retrieval aims to retrieve relevant data from another modality when given a
query of one modality. Although most existing methods that rely on the label information of …

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 …