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3D60 (Up Viewpoint)

Zioulis, Nikolaos; Karakottas, Antonis; Zarpalas, Dimitrios; Daras, Petros


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  <identifier identifierType="DOI">10.5281/zenodo.3408441</identifier>
  <creators>
    <creator>
      <creatorName>Zioulis, Nikolaos</creatorName>
      <givenName>Nikolaos</givenName>
      <familyName>Zioulis</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-7898-9344</nameIdentifier>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
    <creator>
      <creatorName>Karakottas, Antonis</creatorName>
      <givenName>Antonis</givenName>
      <familyName>Karakottas</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-0328-8671</nameIdentifier>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
    <creator>
      <creatorName>Zarpalas, Dimitrios</creatorName>
      <givenName>Dimitrios</givenName>
      <familyName>Zarpalas</familyName>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
    <creator>
      <creatorName>Daras, Petros</creatorName>
      <givenName>Petros</givenName>
      <familyName>Daras</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3814-6710</nameIdentifier>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
  </creators>
  <titles>
    <title>3D60 (Up Viewpoint)</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Spherical Panorama</subject>
    <subject>360</subject>
    <subject>Omnidirectional Image</subject>
    <subject>Omnidirectional Stereo</subject>
    <subject>Stereo Vision</subject>
    <subject>Depth Estimation</subject>
    <subject>Surface Estimation</subject>
    <subject>Synthetic Data</subject>
    <subject>Indoor Scenes</subject>
    <subject>Scene Understanding</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-09-14</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3408441</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsSupplementedBy">10.5281/zenodo.3407840</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3408440</relatedIdentifier>
  </relatedIdentifiers>
  <version>1.0.0</version>
  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/restrictedAccess">Restricted Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Modern 3D vision advancements rely on data driven methods and thus, task specific annotated datasets. Especially for geometric inference tasks like depth and surface estimation, the collection of high quality data is very challenging, expensive and laborious. While considerable efforts have been made for traditional pinhole cameras, the same cannot be said for omnidirectional ones.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;3D60&lt;/strong&gt;&amp;nbsp;is a collective dataset generated in the context of various 360&lt;sup&gt;o&lt;/sup&gt;&amp;nbsp;vision research works. It comprises multi-modal omnidirectional stereo renders of scenes from realistic and synthetic large-scale 3D datasets (&lt;em&gt;Matterport3D&lt;/em&gt;,&amp;nbsp;&lt;em&gt;Stanford2D3D&amp;nbsp;&lt;/em&gt;and&amp;nbsp;&lt;em&gt;SunCG&lt;/em&gt;).&lt;/p&gt;

&lt;p&gt;Our dataset fills a very important gap in data-driven spherical 3D vision and, more specifically, for the monocular and stereo dense depth and surface estimation tasks.&lt;/p&gt;

&lt;p&gt;We originate by exploiting the efforts made in providing synthetic and real scanned 3D datasets of interior spaces and re-using them via ray-tracing in order to generate high quality, densely annotated spherical panoramas.&lt;/p&gt;</description>
    <description descriptionType="Other">Instructions, code and data splits available @ https://vcl3d.github.io/3D60/</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/761934/">761934</awardNumber>
      <awardTitle>Enriching 360 media with 3D storytelling and personalisation elements</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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