ECO: Entity-level captioning in context

Hyunsouk Cho, Seung Won Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Visual scene understanding has been one of the major goals of computer vision. However, existing work has focused on the object-level understanding, which limits the visual questions that can be answered. The goal of this paper is to invite collective efforts for entity-level understanding of images, by releasing ECO datasets and baselines for this task.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
EditorsRavi Kumar, James Caverlee, Hanghang Tong
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages750-751
Number of pages2
ISBN (Electronic)9781509028467
DOIs
Publication statusPublished - 2016 Nov 21
Event2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States
Duration: 2016 Aug 182016 Aug 21

Publication series

NameProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

Other

Other2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
CountryUnited States
CitySan Francisco
Period16/8/1816/8/21

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Sociology and Political Science
  • Communication

Fingerprint Dive into the research topics of 'ECO: Entity-level captioning in context'. Together they form a unique fingerprint.

  • Cite this

    Cho, H., & Hwang, S. W. (2016). ECO: Entity-level captioning in context. In R. Kumar, J. Caverlee, & H. Tong (Eds.), Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 (pp. 750-751). [7752321] (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASONAM.2016.7752321