Document Visual Question Answering


Document Visual Question Answering (DocVQA) seeks to inspire a “purpose-driven” point of view in Document Analysis and Recognition research, where the document content is extracted and used to respond to high-level tasks defined by the human consumers of this information. To this end we organize a series of challenges and release datasets to enable machines "understand" document images and thereby answer questions asked on them.


  • [Aug 2021] Invited speakers for DocVQA workshop are finalized . Check the workshop webpage

  • [April 2021] InfographicVQA arXiv preprint available now

  • [April 2021] 2021 Edition of the DocVQA challenge concludes and leaderboards are public now

  • [November 2020] 2021 Edition of DocVQA challenge begins

  • [June 2020] Presentation of competition summary and overview of DocVQA 2020 challenge and announcement of prizes at the CVPR 2020 workshop

  • [May 2020] - DocVQA 2020 Challenge ends and results are published



MInesh Mathew

IIIT Hyderabad

Rubén Pérez Tito

CVC, University of Barcelona

Dimostheins Karatzas

CVC, University of Barcelona

R. Manmatha


C. V. Jawhar

IIIT Hyderbad


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