Combining geometric, textual and visual features for predicting prepositions in image descriptions
Document typeConference report
Rights accessOpen Access
We investigate the role that geometric, textual and visual features play in the task of predicting a preposition that links two visual entities depicted in an image. The task is an important part of the subsequent process of generating image descriptions. We explore the prediction of prepositions for a pair of entities, both in the case when the labels of such entities are known and unknown. In all situations we found clear evidence that all three features contribute to the prediction task.
CitationRamisa, A., Wang, J., Lu, Y., Dellandrea, E., Moreno-Noguer, F., Gaizauskas, R. Combining geometric, textual and visual features for predicting prepositions in image descriptions. A: Joint SIGDAT Conference on Empirical Methods in Natural Language Processing. "Proceedings of the 2015 EMNLP Conference on Empirical Methods in Natural Language Processing". Lisboa: 2016, p. 214-220.