PosterBot: A System for Generating Posters of Scientific Papers with Neural Models

Abstract

Posters are broadly used to present the important points of academic papers and can be seen as a special form of document summarization. However, the problem of automatic poster generation is under-investigated. In this paper, we present PosterBot, an automatic poster generation system for academic papers. Given a scholarly paper, PosterBot takes three steps to generate the poster. It first selects the most important sections, and then generates corresponding panels from them. Finally, all panels are integrated to get the complete poster. The demonstration shows the efficacy of our proposed system.