X Li, J Yang, J Ma - Neurocomputing, 2021 - Elsevier
With the development of Internet technology and the popularity of digital devices, Content- Based Image Retrieval (CBIR) has been quickly developed and applied in various fields …
SR Dubey - IEEE Transactions on Circuits and Systems for …, 2021 - ieeexplore.ieee.org
The content based image retrieval aims to find the similar images from a large scale dataset against a query image. Generally, the similarity between the representative features of the …
H Lu, M Zhang, X Xu, Y Li… - IEEE transactions on fuzzy …, 2020 - ieeexplore.ieee.org
Hashing methods for efficient image retrieval aim at learning hash functions that map similar images to semantically correlated binary codes in the Hamming space with similarity well …
JT Hoe, KW Ng, T Zhang, CS Chan… - Advances in Neural …, 2021 - proceedings.neurips.cc
A deep hashing model typically has two main learning objectives: to make the learned binary hash codes discriminative and to minimize a quantization error. With further …
Person re-identification (re-ID) has become increasingly popular in the community due to its application and research significance. It aims at spotting a person of interest in other …
Learning to hash has been widely applied to approximate nearest neighbor search for large- scale multimedia retrieval, due to its computation efficiency and retrieval quality. Deep …
In this paper, we present a new hashing method to learn compact binary codes for highly efficient image retrieval on large-scale datasets. While the complex image appearance …
QY Jiang, WJ Li - Proceedings of the IEEE conference on …, 2017 - openaccess.thecvf.com
Due to its low storage cost and fast query speed, cross-modal hashing (CMH) has been widely used for similarity search in multimedia retrieval applications. However, most existing …