# Document Visual Question Answering Challenge 2020

Source: [Document Visual Question Answering Challenge 2020](<https://www.sota2.com/research/paper/68fa6a621e209131cea27e8e>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:24:37.002Z

Authors: Minesh Mathew, Ruben Tito, Dimosthenis Karatzas, R. Manmatha, C.V. Jawahar

Published: 2020-08-20T11:36:36.000Z

## Abstract

This paper presents results of Document Visual Question Answering Challenge organized as part of "Text and Documents in the Deep Learning Era" workshop, in CVPR 2020. The challenge introduces a new problem - Visual Question Answering on document images. The challenge comprised two tasks. The first task concerns with asking questions on a single document image. On the other hand, the second task is set as a retrieval task where the question is posed over a collection of images. For the task 1 a new dataset is introduced comprising 50,000 questions-answer(s) pairs defined over 12,767 document images. For task 2 another dataset has been created comprising 20 questions over 14,362 document images which share the same document template.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2008.08899>)

[PDF](<https://arxiv.org/pdf/2008.08899.pdf>)