With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval
methods struggle to meet the needs of users seeking access to data across various …

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

Hashing has been widely used for large-scale approximate nearest neighbor search
because of its storage and search efficiency. Recent work has found that deep supervised …

Multi-modal hashing is an effective technique to support large-scale multimedia retrieval,
due to its capability of encoding heterogeneous multi-modal features into compact and …

With the prevalence of multimedia content on the Web which usually continuously comes in
a stream fashion, online cross-modal hashing methods have attracted extensive interest in …

Multi-modal hashing fuses multi-modal features at both offline training and online query
stage for compact binary hash learning. It has aroused extensive attention in research filed …

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

As an emerging technology to support scalable content-based image retrieval (CBIR),
hashing has recently received great attention and became a very active research domain. In …

Online hashing technology has attracted extensive attention owing to its effectiveness and
efficiency in processing large-scale streaming data. However, there are still some …

Unsupervised hashing can desirably support scalable content-based image retrieval for its
appealing advantages of semantic label independence, memory, and search efficiency …