Recently, contrastive learning (CL) is a promising way of learning discriminative
representations from time series data. In the representation hierarchy, semantic information …

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

Recently, image-text matching has attracted more and more attention from academia and
industry, which is fundamental to understanding the latent correspondence across visual …

Cross-modal retrieval has been a compelling topic in the multimodal community. Recently,
to mitigate the high cost of data collection, the co-occurred pairs (eg, image and text) could …

Unsupervised anomaly detection is an important research direction in the process of
unsupervised knowledge acquisition. It has been successfully applied in many fields, such …

With the rapid development of science and technology, all types of mixed media contain
large amounts of data. Traditional single multimedia data can no longer satisfy daily …

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 …

Recently, with the advent of Metaverse and AI Generated Content, cross-modal retrieval
becomes popular with a burst of 2D and 3D data. However, this problem is challenging …

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 …

Image set classification (ISC) has always been an active topic, primarily due to the fact that
image set can provide more comprehensive information to describe a subject. However, the …