2 datasets found
  1. E

    TextVQA

    • live.european-language-grid.eu
    • huggingface.co
    json
    Updated Dec 30, 2019
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    (2019). TextVQA [Dataset]. https://live.european-language-grid.eu/catalogue/corpus/5195
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 30, 2019
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    TextVQA requires models to read and reason about text in images to answer questions about them. Specifically, models need to incorporate a new modality of text present in the images and reason over it to answer TextVQA questions.

  2. O

    TextVQA

    • opendatalab.com
    zip
    Updated Sep 22, 2022
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    Georgia Institute of Technology (2022). TextVQA [Dataset]. https://opendatalab.com/OpenDataLab/TextVQA
    Explore at:
    zip(8179095609 bytes)Available download formats
    Dataset updated
    Sep 22, 2022
    Dataset provided by
    Georgia Institute of Technology
    Facebook Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    TextVQA is a dataset to benchmark visual reasoning based on text in images. TextVQA requires models to read and reason about text in images to answer questions about them. Specifically, models need to incorporate a new modality of text present in the images and reason over it to answer TextVQA questions. Statistics

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
(2019). TextVQA [Dataset]. https://live.european-language-grid.eu/catalogue/corpus/5195

TextVQA

Explore at:
jsonAvailable download formats
Dataset updated
Dec 30, 2019
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

TextVQA requires models to read and reason about text in images to answer questions about them. Specifically, models need to incorporate a new modality of text present in the images and reason over it to answer TextVQA questions.

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