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Visual storytelling aims to generate a narrative paragraph from a sequence ofimages automatically. Existing approaches construct text descriptionindependently for each image and roughly concatenate them as a story, whichleads to the problem of generating semantically incoherent content. In thispaper, we propose a new way for visual storytelling by introducing a topicdescription task to detect the global semantic context of an image stream. Astory is then constructed with the guidance of the topic description. In orderto combine the two generation tasks, we propose a multi-agent communicationframework that regards the topic description generator and the story generatoras two agents and learn them simultaneously via iterative updating mechanism.We validate our approach on VIST dataset, where quantitative results,ablations, and human evaluation demonstrate our method's good ability ingenerating stories with higher quality compared to state-of-the-art methods.

Keep it Consistent: Topic-Aware Storytelling from an Image Stream via Iterative Multi-agent Communication