With the development of video network, image set classification (ISC) has received a lot of
attention and can be used for various practical applications, such as video based …

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 …

Compact hash codes can facilitate large-scale multimedia retrieval, significantly reducing
storage and computation. Most hashing methods learn hash functions based on the data …

With the development of vision technology, image set classification (ISC) has flourished in
the image processing field. Different from the one-shot image classification, ISC focuses on …

Zero-shot hashing targets to learn the hash codes of images in unseen classes based on the
limited training data provided by seen classes. In zero-shot hashing, transferring the …

Semantic hashing enables computation and memory-efficient image retrieval through
learning similarity-preserving binary representations. Most existing hashing methods mainly …

Cross-media hashing, which encodes data points from different modalities into a common
Hamming space, has been successfully applied to solve large-scale multimedia retrieval …

Online cross-modal hashing has received increasing research attention due to its capability
of encoding streaming data and updating hash functions simultaneously. Despite significant …

Given that retrieval and storage have compelling efficiency, similarity-preserving hashing
has been extensively employed to approximate nearest neighbor search in large-scale …

Deep Cross-Modal Hashing (CMH) has become one of the most popular solutions for cross-
modal retrieval. Existing methods need to first collect data and then be trained with these …