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Improvement of Normal Estimation for PointClouds via Simplifying Surface Fitting
Firstly, a dynamic top-k selection strategy is introduced to better focus on the most critical points of a given patch, and the points selected by our learning method tend to fit a surface by way of a simple tangent plane, which can dramatically improve the normal estimation results of patches with sharp corners or complex patterns.
Fast and Accurate Normal Estimation for Point Cloud via Patch Stitching
At the stitching stage, we use the learned weights of multi-branch planar experts and distance weights between points to select the best normal from the overlapping parts.
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