July 14, 2021 Dataset Open Access

Sylvain Lobry; Begüm Demir; Devis Tuia

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  <dc:creator>Sylvain Lobry</dc:creator>
  <dc:creator>Begüm Demir</dc:creator>
  <dc:creator>Devis Tuia</dc:creator>
  <dc:date>2021-07-14</dc:date>
  <dc:description>Visual Question Answering is a new task that can facilitate the extraction of information from images through textual queries: it aims at answering an open-ended question formulated in natural language about a given image. In this work, we introduce a new dataset to tackle the task of visual question answering on remote sensing images: this large-scale, open access dataset extracts image/question/answer triplets from the BigEarthNet dataset.This new dataset contains close to 15 millions samples and is openly available</dc:description>
  <dc:identifier>https://zenodo.org/record/5083738</dc:identifier>
  <dc:identifier>10.5281/zenodo.5083738</dc:identifier>
  <dc:identifier>oai:zenodo.org:5083738</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>doi:10.5281/zenodo.5083737</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Visual Question Answering</dc:subject>
  <dc:subject>Remote Sensing</dc:subject>
  <dc:subject>Sentinel 2</dc:subject>
  <dc:title>RSVQAxBEN</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>