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Region-DH: Region-based Deep Hashing for Multi-Instance Aware Image Retrieval

Lookup NU author(s): Dr Bo WeiORCiD


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© 2020 IEEE. This paper introduces an instance-aware hashing approach Region-DH for large-scale multi-label image retrieval. The accurate object bounds can significantly increase the hashing performance of instance features. We design a unified deep neural network that simultaneously localizes and recognizes objects while learning the hash functions for binary codes. Region-DH focuses on recognizing objects and building compact binary codes that represent more foreground patterns. Region-DH can flexibly be used with existing deep neural networks or more complex object detectors for image hashing. Extensive experiments are performed on benchmark datasets and show the efficacy and robustness of the proposed Region-DH model.

Publication metadata

Author(s): Romuald Fotso Mtope F, Wei B

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2020)

Year of Conference: 2020

Online publication date: 28/09/2020

Acceptance date: 02/04/2018

ISSN: 2161-4407

Publisher: IEEE


DOI: 10.1109/IJCNN48605.2020.9207485

Library holdings: Search Newcastle University Library for this item

ISBN: 9781728169262