  Synthesizing realistic images from text descriptions on a dataset like
Microsoft Common Objects in Context (MS COCO), where each image can contain
several objects, is a challenging task. Prior work has used text captions to
generate images. However, captions might not be informative enough to capture
the entire image and insufficient for the model to be able to understand which
objects in the images correspond to which words in the captions. We show that
adding a dialogue that further describes the scene leads to significant
improvement in the inception score and in the quality of generated images on
the MS COCO dataset.
