Cross-validating Image Description Datasets and Evaluation Metrics

Josiah Wang, Robert Gaizauskas


Abstract
The task of automatically generating sentential descriptions of image content has become increasingly popular in recent years, resulting in the development of large-scale image description datasets and the proposal of various metrics for evaluating image description generation systems. However, not much work has been done to analyse and understand both datasets and the metrics. In this paper, we propose using a leave-one-out cross validation (LOOCV) process as a means to analyse multiply annotated, human-authored image description datasets and the various evaluation metrics, i.e. evaluating one image description against other human-authored descriptions of the same image. Such an evaluation process affords various insights into the image description datasets and evaluation metrics, such as the variations of image descriptions within and across datasets and also what the metrics capture. We compute and analyse (i) human upper-bound performance; (ii) ranked correlation between metric pairs across datasets; (iii) lower-bound performance by comparing a set of descriptions describing one image to another sentence not describing that image. Interesting observations are made about the evaluation metrics and image description datasets, and we conclude that such cross-validation methods are extremely useful for assessing and gaining insights into image description datasets and evaluation metrics for image descriptions.
Anthology ID:
L16-1489
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
3059–3066
Language:
URL:
https://aclanthology.org/L16-1489
DOI:
Bibkey:
Cite (ACL):
Josiah Wang and Robert Gaizauskas. 2016. Cross-validating Image Description Datasets and Evaluation Metrics. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 3059–3066, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Cross-validating Image Description Datasets and Evaluation Metrics (Wang & Gaizauskas, LREC 2016)
Copy Citation:
PDF:
https://aclanthology.org/L16-1489.pdf
Data
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