  Image narrative generation is a task to create a story from an image with a
subjective viewpoint. Given the importance of the subjective feelings of
writers, readers, and characters in storytelling, an image narrative generation
method should consider human emotion. In this study, we propose a novel method
of image narrative generation called ViNTER (Visual Narrative Transformer with
Emotion arc Representation), which takes "emotion arc" as input to capture a
sequence of emotional changes. Since emotion arcs represent the trajectory of
emotional change, it is expected that we can include detailed information about
the emotional changes in the story to the model. We present experimental
results of both automatic and manual evaluations on the Image Narrative dataset
and demonstrate the effectiveness of the proposed approach.
