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        <identifier>oai:ipsj.ixsq.nii.ac.jp:00216153</identifier>
        <datestamp>2025-01-19T15:54:26Z</datestamp>
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          <dc:title>Bilateral Normal Integration</dc:title>
          <dc:title xml:lang="en">Bilateral Normal Integration</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>Xu, Cao</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>Hiroaki, Santo</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>Boxin, Shi</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>Yasuyuki, Matsushita</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Xu, Cao</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Hiroaki, Santo</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Boxin, Shi</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Yasuyuki, Matsushita</jpcoar:creatorName>
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          <jpcoar:subject subjectScheme="Other">画像処理・機械学習</jpcoar:subject>
          <datacite:description descriptionType="Other">This paper studies the discontinuity preservation problem in the task of surface recovery by integrating a single-view surface normal map. Although various sophisticated strategies have been proposed, this challenging problem has not been well solved due to unknown discontinuity positions in the normal map. The key of our method is to model the existence of discontinuity between every two adjacent pixels by the depth differences between that two pixels. At each pixel, we approximate the left and right (resp., upper and lower) partial derivatives and relatively weight the two approximations by comparing the depth differences at the left and right (resp., upper and lower) sides. Therefore we term our method as “bilateral” normal integration. By iteratively solving for the depths and updating the discontinuity maps, we can recover the surface with discontinuities. Experiments on various challenging surfaces demonstrate our method's effectiveness. In addition, we show that discontinuities can be preserved in perspective normal maps by our method.</datacite:description>
          <datacite:description descriptionType="Other">This paper studies the discontinuity preservation problem in the task of surface recovery by integrating a single-view surface normal map. Although various sophisticated strategies have been proposed, this challenging problem has not been well solved due to unknown discontinuity positions in the normal map. The key of our method is to model the existence of discontinuity between every two adjacent pixels by the depth differences between that two pixels. At each pixel, we approximate the left and right (resp., upper and lower) partial derivatives and relatively weight the two approximations by comparing the depth differences at the left and right (resp., upper and lower) sides. Therefore we term our method as “bilateral” normal integration. By iteratively solving for the depths and updating the discontinuity maps, we can recover the surface with discontinuities. Experiments on various challenging surfaces demonstrate our method's effectiveness. In addition, we show that discontinuities can be preserved in perspective normal maps by our method.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2022-01-20</datacite:date>
          <dc:language>eng</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_18gh">technical report</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/216153</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">2188-8701</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AA11131797</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告コンピュータビジョンとイメージメディア（CVIM）</jpcoar:sourceTitle>
          <jpcoar:volume>2022-CVIM-228</jpcoar:volume>
          <jpcoar:issue>17</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>8</jpcoar:pageEnd>
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            <jpcoar:extent>39.4 MB</jpcoar:extent>
            <datacite:date dateType="Available">2024-01-20</datacite:date>
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