Hashing method maps similar high-dimensional data to binary hashcodes with smaller
hamming distance, and it has received broad attention due to its low storage cost and fast …

In this paper, we propose a Deep Hashing method with Active Pairwise Supervision (DH-
APS). Conventional methods with passive pairwise supervision obtain labeled data for …

Hashing is a popular search algorithm for its compact binary representation and efficient
Hamming distance calculation. Benefited from the advance of deep learning, deep hashing …

Unsupervised hashing method aims to generate compact binary hash codes for images
without label supervision. Existing unsupervised hashing methods usually learn binary hash …

Deep hashing has attracted considerable attention to tackle large-scale retrieval tasks,
because of automatic and powerful feature extraction of convolutional neural networks and …

Recently, deep learning has been successfully applied to the problem of hashing, yielding
remarkable performance compared to traditional methods with hand-crafted features …

Hashing is regarded as an efficient approach for image retrieval and many other big-data
applications. Recently, deep learning frameworks are adopted for image hashing …

Similarity-preserved hashing has become a popular technique for large-scale image
retrieval because of its low storage cost and high search efficiency. Unsupervised hashing …

In this paper, we propose a simple yet effective relaxation-free method to learn more
effective binary codes via policy gradient for scalable image search. While a variety of deep …

Hashing has attracted increasing attention in image retrieval recently due to its storage and
computational efficiency. Although several deep unsupervised hashing methods have been …