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    <identifier>10.57760/sciencedb.32337</identifier>
    <datestamp>2025-12-19T14:42:09Z</datestamp>
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  <dc:date>2025-12-19</dc:date>
  <dc:title>OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 5)</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.32337</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.</dc:description>
  <dc:subject>dataset; relighting; Photometric Stereo; 3D reconstruction</dc:subject>
  <dc:creator>Fan Pei</dc:creator>
  <dc:creator>Jinchen Bai</dc:creator>
  <dc:creator>Xiang Feng</dc:creator>
  <dc:creator>Zoubin Bi</dc:creator>
  <dc:creator>Kun Zhou</dc:creator>
  <dc:creator>Hongzhi Wu</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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