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Found 3 papers, 1 papers with code
High-Fidelity Point Cloud Completion with Low-Resolution Recovery and Noise-Aware Upsampling
Instead of decoding a whole shape, we propose to decode and refine a low-resolution (low-res) point cloud first, and then performs a patch-wise noise-aware upsampling rather than interpolating the whole sparse point cloud at once, which tends to lose details.
PRS-Net: Planar Reflective Symmetry Detection Net for 3D Models
In this paper, we present a novel learning framework to automatically discover global planar reflective symmetry of a 3D shape.
Sparse Data Driven Mesh Deformation
This along with a suitably chosen deformation basis including spatially localized deformation modes leads to significant advantages, including more meaningful, reliable, and efficient deformations because fewer and localized deformation modes are applied.
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