Feature hashing

Pattern recognition (psychology)

Image (mathematics)

Discriminative model

Computer science

Double hashing

Image retrieval

Machine learning

Dynamic perfect hashing

Scalability

Hash table

Theoretical computer science

Deep learning

Artificial intelligence

Computer security

Database

Universal hashing

Hash function

IEEE Transactions on Image Processing

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 current advances in deep learning, supervised deep hashing methods have greatly boosted the retrieval performance, under the strong supervision of large amounts of manually annotated semantic labels. However, their performance is highly dependent upon the supervised labels, which significantly limits the scalability. In contrast, unsupervised deep hashing without label dependence enjoys the advantages of well scalability. Nevertheless, due to the relaxed hash optimization, and more importantly, the lack of semantic guidance, existing methods suffer from limited retrieval performance. In this paper, we propose a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SCAlable Deep Hashing</i> (SCADH) to learn enhanced hash codes for social image retrieval. We formulate a unified scala...

Scalable Deep Hashing for Large-Scale Social Image Retrieval