ExchNet: A Unified Hashing Network for Large-Scale Fine-Grained Image Retrieval

Quan Cui, Qing Yuan Jiang, Xiu Shen Wei, Wu Jun Li, Osamu Yoshie

研究成果: Conference contribution

抄録

Retrieving content relevant images from a large-scale fine-grained dataset could suffer from intolerably slow query speed and highly redundant storage cost, due to high-dimensional real-valued embeddings which aim to distinguish subtle visual differences of fine-grained objects. In this paper, we study the novel fine-grained hashing topic to generate compact binary codes for fine-grained images, leveraging the search and storage efficiency of hash learning to alleviate the aforementioned problems. Specifically, we propose a unified end-to-end trainable network, termed as ExchNet. Based on attention mechanisms and proposed attention constraints, ExchNet can firstly obtain both local and global features to represent object parts and the whole fine-grained objects, respectively. Furthermore, to ensure the discriminative ability and semantic meaning’s consistency of these part-level features across images, we design a local feature alignment approach by performing a feature exchanging operation. Later, an alternating learning algorithm is employed to optimize the whole ExchNet and then generate the final binary hash codes. Validated by extensive experiments, our ExchNet consistently outperforms state-of-the-art generic hashing methods on five fine-grained datasets. Moreover, compared with other approximate nearest neighbor methods, ExchNet achieves the best speed-up and storage reduction, revealing its efficiency and practicality.

本文言語English
ホスト出版物のタイトルComputer Vision – ECCV 2020 - 16th European Conference 2020, Proceedings
編集者Andrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm
出版社Springer Science and Business Media Deutschland GmbH
ページ189-205
ページ数17
ISBN(印刷版)9783030585792
DOI
出版ステータスPublished - 2020
イベント16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom
継続期間: 2020 8 232020 8 28

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12348 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference16th European Conference on Computer Vision, ECCV 2020
CountryUnited Kingdom
CityGlasgow
Period20/8/2320/8/28

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

フィンガープリント 「ExchNet: A Unified Hashing Network for Large-Scale Fine-Grained Image Retrieval」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル