Learning Implicit Fields for Point Cloud Filtering
Since point clouds acquired by scanners inevitably contain noise, recovering a clean version from a noisy point cloud is essential for further 3D geometry processing applications. Several data-driven approaches have been recently introduced to overcome the drawbacks of traditional filtering algorith...
Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - PP(2024) vom: 27. Aug. |
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Format: | Online-Aufsatz |
Sprache: | English |
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2024
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Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
Schlagworte: | Journal Article |
Online verfügbar |
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