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 exponential surge in diverse multimodal data, traditional unimodal retrieval
methods struggle to meet the needs of users seeking access to data across various …

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 …

Recently deep cross-modal hashing (CMH) have received increased attention in multimedia
information retrieval, as it is able to combine the benefit from the low storage cost and search …

The recent deep cross-modal hashing (DCMH) has achieved superior performance in
effective and efficient cross-modal retrieval and thus has drawn increasing attention …

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 …

Sketch-based image retrieval (SBIR) is challenging due to the inherent domain-gap
between sketch and photo. Compared with pixel-perfect depictions of photos, sketches are …

The heterogeneity-gap between different modalities brings a significant challenge to
multimedia information retrieval. Some studies formalize the cross-modal retrieval tasks as a …

Deep cross-modal hashing which integrates deep learning and hashing into cross-modal
retrieval, achieves better performance than traditional cross-modal retrieval methods …

This paper contributes a new large-scale dataset for weakly supervised cross-media
retrieval, named Twitter100k. Current datasets, such as Wikipedia, NUS Wide, and Flickr30k …