Framing Image Description as a Ranking Task: Data, Models and Evaluation Metrics (Extended Abstract)
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Journal Track. Pages 4188-4191.
Abstract
In [Hodosh et al., 2013], we established a ranking based framework for sentence-based image description and retrieval. We introduce a new dataset of images paired with multiple descriptive captions that was specifically designed for these tasks. We also present strong KCCA-based baseline systems for description and search, and perform an in-depth study of evaluation metrics for these two tasks. Our results indicate that automatic evaluation metrics for our ranking-based tasks are more accurate and robust than those proposed for generation-based image description.
@inproceedings{ijcai2015p593,
title = {Framing Image Description as a Ranking Task: Data, Models and Evaluation Metrics (Extended Abstract)},
author = {Hodosh, Micah and Young, Peter and Hockenmaier, Julia},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {4188--4191},
year = {2015},
month = {7},
note = {Journal Track},
url = {https://ijcai.org/proceedings/2015/593},
}
TY - CPAPER TI - Framing Image Description as a Ranking Task: Data, Models and Evaluation Metrics (Extended Abstract) AU - Hodosh, Micah AU - Young, Peter AU - Hockenmaier, Julia T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 4188 EP - 4191 UR - https://ijcai.org/proceedings/2015/593 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: