  Modern image captioning system relies heavily on extracting knowledge from
images to capture the concept of a static story. In this paper, we propose a
textual visual context dataset for captioning, in which the publicly available
dataset COCO Captions (Lin et al., 2014) has been extended with information
about the scene (such as objects in the image). Since this information has a
textual form, it can be used to leverage any NLP task, such as text similarity
or semantic relation methods, into captioning systems, either as an end-to-end
training strategy or a post-processing based approach.
