With the explosive growth of multimedia contents, multimedia retrieval is facing
unprecedented challenges on both storage cost and retrieval speed. Hashing technique can …

Unsupervised feature selection chooses a subset of discriminative features to reduce feature
dimension under the unsupervised learning paradigm. Although lots of efforts have been …

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 …

Recent years have witnessed the wide application of hashing for large-scale image retrieval,
because of its high computation efficiency and low storage cost. Particularly, benefiting from …

Owing to its query and storage efficiency, hash learning has sparked much interest for Cross-
Modal Retrieval (CMR) task. Previous literatures have proved the superiority of supervised …

Unsupervised cross-modal hashing has attracted considerable attention to support large-
scale cross-modal retrieval. Although promising progresses have been made so far, existing …

Supervised cross-modal hashing has attracted much attention. However, there are still some
challenges, eg, how to effectively embed the label information into binary codes, how to …

With the dramatic increase in the amount of multimedia data, cross-modal similarity retrieval
has become one of the most popular yet challenging problems. Hashing offers a promising …

Hashing methods have captured much attention for cross-modal retrieval in recent years.
Most existing approaches mainly focus on preserving the semantic similarity across …

Image quality assessment (IQA) is an important task of image processing and has diverse
applications, such as image super-resolution reconstruction, image transmission and …