Nearest neighbor search aims at obtaining the samples in the database with the smallest
distances from them to the queries, which is a basic task in a range of fields, including …

Recently, numerous unsupervised cross-modal hashing methods have been proposed to
deal the image-text retrieval tasks for the unlabeled cross-modal data. However, when these …

The high efficiency in computation and storage makes hashing (including binary hashing
and quantization) a common strategy in large-scale retrieval systems. To alleviate the …

Cross-modal hashing has been widely used in multimedia retrieval tasks due to its fast
retrieval speed and low storage cost. Recently, many deep unsupervised cross-modal …

In this paper, we investigate the problem of unsupervised domain adaptive hashing, which
leverage knowledge from a label-rich source domain to expedite learning to hash on a label …

Unsupervised hashing is an important approach for large-scale content-based remote
sensing (RS) image retrieval. Existing unsupervised hashing methods usually utilize data …

Hashing has become increasingly popular in approximate nearest neighbor search in recent
years due to its storage and computational efficiency. While deep unsupervised hashing has …

The majority of deep unsupervised hashing methods usually first construct pairwise
semantic similarity information and then learn to map images into compact hash codes while …

Recently, deep supervised hashing methods have shown state-of-the-art performance by
integrating feature learning and hash codes learning into an end-to-end network to generate …

Deep hashing has been widely used in multimedia retrieval systems due to its storage and
computation efficiency. Unsupervised hashing has received a lot of attention in recent years …