… Unlike most existing cross-modal hashing methods which usually relax the … hash codes,
we develop a discrete optimization framework to jointly learn binary codes and a series of hash …

… Specifically, we perform cross-modal retrieval on a training set with the learnt hash codes,
using one as a query and the rest as the retrieval set every time, and then measure the …

… Therefore, it is still desirable to study a fast and discriminative cross-modal hashing method
from a practical viewpoint. In this article, we present a fast discriminative discrete hashing (…

… And they usually use a relax constraint of hash code which … , a hashing method called
Deep Adversarial Discrete Hashing (DADH) is proposed to address these issues for cross-modal …

… shortcomings of existing cross-modal hashing methods, in this paper, we propose a novel
nonlinear robust discrete hashing method, named Nonlinear Robust Discrete Hashing (NRDH)…

… complex optimization of hash codes, leading to … Discrete Latent Factor model-based
cross-modal Hashing (DLFH), we propose a novel cross-modal online hashing method, ie, Discrete …

… , we propose a novel nonlinear discrete cross-modal hashing framework consisting of …
discrete learning scheme for semantic similarity preservation. The proposed nonlinear hashing …

… of hashing … cross-modal hashing is the best choice when the quality of the labels is good.
Our method belongs to supervised cross-modal hashing, and compared with other hashing …

… (the size is n × n), reducing computing complexity and the cost of memory, as well as
enhancing discriminatory power of the hash codes. We also develop a discrete hash optimization …

… We propose an end-to-end learning framework to learn discrete hashing code for cross-modal
retrieval with multiple supervision. It supervises the feature learning process with the joint …