  Infographics are documents designed to effectively communicate information
using a combination of textual, graphical and visual elements. In this work, we
explore the automatic understanding of infographic images by using Visual
Question Answering technique.To this end, we present InfographicVQA, a new
dataset that comprises a diverse collection of infographics along with natural
language questions and answers annotations. The collected questions require
methods to jointly reason over the document layout, textual content, graphical
elements, and data visualizations. We curate the dataset with emphasis on
questions that require elementary reasoning and basic arithmetic skills.
Finally, we evaluate two strong baselines based on state of the art multi-modal
VQA models, and establish baseline performance for the new task. The dataset,
code and leaderboard will be made available at http://docvqa.org
