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Computer Science > Computer Vision and Pattern Recognition

arXiv:2104.12756 (cs)
[Submitted on 26 Apr 2021 (v1), last revised 22 Aug 2021 (this version, v2)]

Title:InfographicVQA

Authors:Minesh Mathew, Viraj Bagal, Rubèn Pérez Tito, Dimosthenis Karatzas, Ernest Valveny, C.V Jawahar
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Abstract: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 this http URL 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 this http URL
Subjects: Computer Vision and Pattern Recognition (cs.CV); Computation and Language (cs.CL)
Cite as: arXiv:2104.12756 [cs.CV]
  (or arXiv:2104.12756v2 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2104.12756

Submission history

From: Minesh Mathew [view email]
[v1] Mon, 26 Apr 2021 17:45:54 UTC (8,825 KB)
[v2] Sun, 22 Aug 2021 04:27:56 UTC (9,222 KB)
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