Recent vision and learning studies show that learning compact hash codes can facilitate
massive data processing with significantly reduced storage and computation. Particularly …

Co-saliency detection, which focuses on extracting commonly salient objects in a group of
relevant images, has been attracting research interest because of its broad applications. In …

The use of multiple features has been shown to be an effective strategy for visual tracking
because of their complementary contributions to appearance modeling. The key problem is …

This paper proposes a deep hashing framework, namely, unsupervised deep video hashing
(UDVH), for large-scale video similarity search with the aim to learn compact yet effective …

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 …

Due to its storage and retrieval efficiency, cross-modal hashing (CMH) has been widely
used for cross-modal similarity search in many multimedia applications. According to the …

To intelligently analyze and understand video content, a key step is to accurately perceive
the motion of the interested objects in videos. To this end, the task of object tracking, which …

Feature extraction (FE) is a crucial research area in hyperspectral image (HSI) processing.
Recently, due to the powerful ability of deep learning (DL) to extract spatial and spectral …

Advanced hashing technique is essential in large scale online image retrieval and
organization, where image contents are frequently changed. While traditional multi-view …

Image set classification has attracted much attention because of its broad applications.
Despite the success made so far, the problems of intra-class diversity and inter-class …