Text-based Visual Question Answering

Text-Based Visual Question Answering is a visual question answering task that specifically requires reasoning over textual elements embedded within images to answer questions, distinguishing it from general visual question answering by its reliance on scene text comprehension.

132

Publications

7.6K

Citations

487

Authors

161

Institutions

Publications per year

2017–2026

119

Authors

487

  1. QW
    Qi Wu

    The University of Adelaide, Australia

    7 publications · 628 citations

    7

    h-index

  2. AV
    Anton van den Hengel

    The University of Adelaide, Australia

    6 publications · 573 citations

    6

    h-index

  3. PW
    Peng Wang

    Northwestern Polytechnical University, China

    5 publications · 543 citations

    5

    h-index

  4. ZY
    Zhengyuan Yang

    University of Rochester, United States

    5 publications · 217 citations

    5

    h-index

  5. CK
    Christopher Kanan

    Rochester Institute of Technology, United States

    4 publications · 661 citations

    4

    h-index

1–5 of 487

Venues

  1. arXiv (Cornell University)

    Repository · 29 publications · 1.7K citations

    17

    h-index

  2. 3

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 210 citations

    3

    h-index

  4. IEEE Transactions on Image Processing

    2 publications · 52 citations

    2

    h-index

  5. 2

    h-index

1–5