Computational visual storytelling produces a textual description of events
and interpretations depicted in a sequence of images. These texts are made
possible by advances and cross-disciplinary approaches in natural language
processing, generation, and computer vision. We define a computational creative
visual storytelling as one with the ability to alter the telling of a story
along three aspects: to speak about different environments, to produce
variations based on narrative goals, and to adapt the narrative to the
audience. These aspects of creative storytelling and their effect on the
narrative have yet to be explored in visual storytelling. This paper presents a
pipeline of task-modules, Object Identification, Single-Image Inferencing, and
Multi-Image Narration, that serve as a preliminary design for building a
creative visual storyteller. We have piloted this design for a sequence of
images in an annotation task. We present and analyze the collected corpus and
describe plans towards automation.

本文提出了一个计算创意视觉叙述的管道和任务模块，用于构建一个具有不同环境，基于叙述目标的变异和面向受众的故事叙述能力的计算机视觉技术，并分析了收集的数据并描述了此方法向自动化的计划。