ECO: Entity-level captioning in context

Hyunsouk Cho, Seungwon 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

Fingerprint

Computer vision

All Science Journal Classification (ASJC) codes

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

Cite this

Cho, H., & Hwang, S. (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
Cho, Hyunsouk ; Hwang, Seungwon. / ECO : Entity-level captioning in context. Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. editor / Ravi Kumar ; James Caverlee ; Hanghang Tong. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 750-751 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016).
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Cho, H & Hwang, S 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., 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., pp. 750-751, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, San Francisco, United States, 16/8/18. https://doi.org/10.1109/ASONAM.2016.7752321

ECO : Entity-level captioning in context. / Cho, Hyunsouk; Hwang, Seungwon.

Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. ed. / Ravi Kumar; James Caverlee; Hanghang Tong. Institute of Electrical and Electronics Engineers Inc., 2016. p. 750-751 7752321 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016).

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

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Cho H, Hwang S. ECO: Entity-level captioning in context. In Kumar R, Caverlee J, Tong H, editors, 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. 2016. p. 750-751. 7752321. (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016). https://doi.org/10.1109/ASONAM.2016.7752321