July 14, 2021 Dataset Open Access

Sylvain Lobry; Begüm Demir; Devis Tuia

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  "description": "<p>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</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "LIPADE, Universit\u00e9 de Paris, Paris, France", 
      "@id": "https://orcid.org/0000-0003-4738-2416", 
      "@type": "Person", 
      "name": "Sylvain Lobry"
    }, 
    {
      "affiliation": "Technische Universit\u00e4t Berlin", 
      "@type": "Person", 
      "name": "Beg\u00fcm Demir"
    }, 
    {
      "affiliation": "Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne, Sion, Switzerland", 
      "@id": "https://orcid.org/0000-0003-0374-2459", 
      "@type": "Person", 
      "name": "Devis Tuia"
    }
  ], 
  "url": "https://zenodo.org/record/5083738", 
  "datePublished": "2021-07-14", 
  "version": "0.1", 
  "keywords": [
    "Visual Question Answering", 
    "Remote Sensing", 
    "Sentinel 2"
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  "identifier": "https://doi.org/10.5281/zenodo.5083738", 
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