Deep binary reconstruction for cross-modal hashing

Xuelong Li, Di Hu, Feiping Nie

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

41 Scopus citations

Abstract

With the increasing demand of massive multimodal data storage and organization, cross-modal retrieval based on hashing technique has drawn much attention nowadays. It takes the binary codes of one modality as the query to retrieve the relevant hashing codes of another modality. However, the existing binary constraint makes it difficult to find the optimal cross-modal hashing function. Most approaches choose to relax the constraint and perform thresholding strategy on the real-value representation instead of directly solving the original objective. In this paper, we first provide a concrete analysis about the effectiveness of multimodal networks in preserving the inter- and intra-modal consistency. Based on the analysis, we provide a so-called Deep Binary Reconstruction (DBRC) network that can directly learn the binary hashing codes in an unsupervised fashion. The superiority comes from a proposed simple but efficient activation function, named as Adaptive Tanh (ATanh). The ATanh function can adaptively learn the binary codes and be trained via back-propagation. Extensive experiments on three benchmark datasets demonstrate that DBRC outperforms several state-of-the-art methods in both image2text and text2image retrieval task.

Original languageEnglish
Title of host publicationMM 2017 - Proceedings of the 2017 ACM Multimedia Conference
PublisherAssociation for Computing Machinery, Inc
Pages1398-1406
Number of pages9
ISBN (Electronic)9781450349062
DOIs
StatePublished - 23 Oct 2017
Event25th ACM International Conference on Multimedia, MM 2017 - Mountain View, United States
Duration: 23 Oct 201727 Oct 2017

Publication series

NameMM 2017 - Proceedings of the 2017 ACM Multimedia Conference

Conference

Conference25th ACM International Conference on Multimedia, MM 2017
Country/TerritoryUnited States
CityMountain View
Period23/10/1727/10/17

Keywords

  • Binary reconstruction
  • Cross-modal hashing
  • Retrieval

Fingerprint

Dive into the research topics of 'Deep binary reconstruction for cross-modal hashing'. Together they form a unique fingerprint.

Cite this