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    <subfield code="a">10.1016/j.dib.2022.108375</subfield>
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  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="a">Berenguel-Baeta, B.</subfield>
    <subfield code="u">Universidad de Zaragoza</subfield>
    <subfield code="0">(orcid)0000-0003-2674-4844</subfield>
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  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">Non-central panorama indoor dataset</subfield>
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    <subfield code="c">2022</subfield>
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    <subfield code="a">Omnidirectional images are one of the main sources of information for learning-based scene understanding algorithms. However, annotated datasets of omnidirectional images cannot keep the pace of these learning-based algorithms development. Among the different panoramas and in contrast to standard central ones, non-central panoramas provide geometrical information in the distortion of the image from which we can retrieve 3D information of the environment. However, due to the lack of commercial non-central devices, up until now there was no dataset of these kind of panoramas. In this data paper, we present the first dataset of non-central panoramas for indoor scene understanding. The dataset is composed of 2574 RGB non-central panoramas taken in around 650 different rooms. Each panorama has associated a depth map and annotations to obtain the layout of the room from the image as a structural edge map, list of corners in the image, the 3D corners of the room and the camera pose. The images are taken from photorealistic virtual environments and pixel-wise automatically annotated.</subfield>
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    <subfield code="a">Multidisciplinary</subfield>
    <subfield code="c">2022</subfield>
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  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Bermudez-Cameo, J.</subfield>
    <subfield code="u">Universidad de Zaragoza</subfield>
    <subfield code="0">(orcid)0000-0002-8479-1748</subfield>
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  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Guerrero, J.J.</subfield>
    <subfield code="u">Universidad de Zaragoza</subfield>
    <subfield code="0">(orcid)0000-0001-5209-2267</subfield>
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    <subfield code="1">5007</subfield>
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    <subfield code="a">Universidad de Zaragoza</subfield>
    <subfield code="b">Dpto. Informát.Ingenie.Sistms.</subfield>
    <subfield code="c">Área Ingen.Sistemas y Automát.</subfield>
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  <datafield tag="773" ind1=" " ind2=" ">
    <subfield code="g">43 (2022), 108375 [5 pp.]</subfield>
    <subfield code="p">Data brief</subfield>
    <subfield code="t">Data in Brief</subfield>
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    <subfield code="a">2023-09-13-14:14:16</subfield>
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