  We explore the use of a knowledge graphs, that capture general or commonsense
knowledge, to augment the information extracted from images by the
state-of-the-art methods for image captioning. The results of our experiments,
on several benchmark data sets such as MS COCO, as measured by CIDEr-D, a
performance metric for image captioning, show that the variants of the
state-of-the-art methods for image captioning that make use of the information
extracted from knowledge graphs can substantially outperform those that rely
solely on the information extracted from images.
