Get 3D object shape using local and global priors learned from data with PPSURF
Get 3D object shape using local and global priors learned from data with PPSURF
PPSURF: Combining Patches and Point Convolutions for Detailed Surface Reconstruction
arXiv paper abstract https://arxiv.org/abs/2401.08518
arXiv PDF paper https://arxiv.org/pdf/2401.08518.pdf
3D surface reconstruction from point clouds is a key step in areas such as content creation, archaeology, digital cultural heritage, and engineering.
Current approaches either try to optimize a non-data-driven surface representation to fit the points, or learn a data-driven prior over the distribution of commonly occurring surfaces and how they correlate with potentially noisy point clouds.
Data-driven methods enable robust handling of noise and typically either focus on a global or a local prior, which trade-off between robustness to noise on the global end and surface detail preservation on the local end.
... propose PPSurf as a method that combines a global prior based on point convolutions and a local prior based on processing local point cloud patches.
... approach is robust to noise while recovering surface details more accurately than the current state-of-the-art ...
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