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 language | English |
|---|---|
| Title of host publication | Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 |
| Editors | Ravi Kumar, James Caverlee, Hanghang Tong |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 750-751 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781509028467 |
| DOIs | |
| Publication status | Published - 2016 Nov 21 |
| Event | 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States Duration: 2016 Aug 18 → 2016 Aug 21 |
Publication series
| Name | Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 |
|---|
Other
| Other | 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 |
|---|---|
| Country | United States |
| City | San Francisco |
| Period | 16/8/18 → 16/8/21 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Sociology and Political Science
- Communication
Cite this
}
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 proceeding › Conference contribution
TY - GEN
T1 - ECO
T2 - Entity-level captioning in context
AU - Cho, Hyunsouk
AU - Hwang, Seungwon
PY - 2016/11/21
Y1 - 2016/11/21
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85006826098&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006826098&partnerID=8YFLogxK
U2 - 10.1109/ASONAM.2016.7752321
DO - 10.1109/ASONAM.2016.7752321
M3 - Conference contribution
AN - SCOPUS:85006826098
T3 - Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
SP - 750
EP - 751
BT - Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
A2 - Kumar, Ravi
A2 - Caverlee, James
A2 - Tong, Hanghang
PB - Institute of Electrical and Electronics Engineers Inc.
ER -