June 18, 2021 Dataset Restricted Access

Albanis, Georgios; Zioulis, Nikolaos; Drakoulis, Petros; Gkitsas, Vasileios; Sterzentsenko, Vladimiros; Alvarez, Federico; Zarpalas, Dimitrios; Daras, Petros

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  <identifier identifierType="DOI">10.5281/zenodo.4986012</identifier>
  <creators>
    <creator>
      <creatorName>Albanis, Georgios</creatorName>
      <givenName>Georgios</givenName>
      <familyName>Albanis</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-2032-6767</nameIdentifier>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
    <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>Drakoulis, Petros</creatorName>
      <givenName>Petros</givenName>
      <familyName>Drakoulis</familyName>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
    <creator>
      <creatorName>Gkitsas, Vasileios</creatorName>
      <givenName>Vasileios</givenName>
      <familyName>Gkitsas</familyName>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
    <creator>
      <creatorName>Sterzentsenko, Vladimiros</creatorName>
      <givenName>Vladimiros</givenName>
      <familyName>Sterzentsenko</familyName>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
    <creator>
      <creatorName>Alvarez, Federico</creatorName>
      <givenName>Federico</givenName>
      <familyName>Alvarez</familyName>
      <affiliation>Universidad Politécnica de Madrid</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>
      <affiliation>Centre for Research and Technology Hellas</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Pano3D: GibsonV2 Full High Resolution</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <subjects>
    <subject>Spherical Depth Estimation</subject>
    <subject>Spherical Panoramas</subject>
    <subject>Omnidirectional Dataset</subject>
    <subject>Benchmark</subject>
    <subject>360</subject>
    <subject>Computer Vision</subject>
    <subject>Deep Learning</subject>
    <subject>Data-driven Methods</subject>
    <subject>3D Vision</subject>
    <subject>Depth Estimation</subject>
    <subject>Geometry Estimation</subject>
    <subject>Surface Orientation Estimation</subject>
    <subject>Indoor Scenes</subject>
    <subject>Scene Understanding</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2021-06-18</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4986012</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4986011</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/atlantis-ar</relatedIdentifier>
  </relatedIdentifiers>
  <version>1.0</version>
  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/restrictedAccess">Restricted Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Pano3D is a new benchmark for depth estimation from spherical panoramas. Its goal is to drive progress for this task in a consistent and holistic manner. To achieve that we generate a new dataset and integrate evaluation metrics that capture not only depth performance, but also secondary traits like boundary preservation and smoothness. Moreover,&amp;nbsp;Pano3D&amp;nbsp;takes a step beyond typical intra-dataset evaluation schemes to inter-dataset performance assessment. By disentangling generalization to three different axes,&amp;nbsp;Pano3D&amp;nbsp;facilitates proper extrapolation assessment under different out-of-training data conditions. Relying on the&amp;nbsp;Pano3D&amp;nbsp;holistic benchmark for 360 depth estimation we perform an extended analysis and derive a solid baseline for the task.&lt;/p&gt;</description>
    <description descriptionType="Other">Dataset with coupled color and depth maps.(normals are not included but may be provided upon request)</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/Horizon 2020 Framework Programme - Innovation action/951900/">951900</awardNumber>
      <awardTitle>AuThoring tooL for indoor Augmented and dimiNished realiTy experIenceS</awardTitle>
    </fundingReference>
  </fundingReferences>
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