Show, Prefer and Tell: Incorporating User Preferences into Image Captioning

Annika Lindh, Robert Ross, John D. Kelleher

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

Abstract

Current image captioning models produce fluent captions, but they rely on a one-size-fits-all approach that does not take into account the preferences of individual end-users. We present a method to generate descriptions with an adjustable amount of content that can be set at inference-time, thus providing a step toward a more user-centered approach to image captioning.

Original languageEnglish
Title of host publicationProceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, SAC 2023
PublisherAssociation for Computing Machinery
Pages1139-1142
Number of pages4
ISBN (Electronic)9781450395175
DOIs
Publication statusPublished - 27 Mar 2023
Event38th Annual ACM Symposium on Applied Computing, SAC 2023 - Tallinn, Estonia
Duration: 27 Mar 202331 Mar 2023

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Conference

Conference38th Annual ACM Symposium on Applied Computing, SAC 2023
Country/TerritoryEstonia
CityTallinn
Period27/03/2331/03/23

Keywords

  • assistive technology
  • deep learning
  • image captioning

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