Survey of surface reconstruction from point clouds with Sulzer

Survey of surface reconstruction from point clouds with Sulzer

A Survey and Benchmark of Automatic Surface Reconstruction from Point Clouds
arXiv paper abstract https://arxiv.org/abs/2301.13656
arXiv PDF paper https://arxiv.org/pdf/2301.13656.pdf
GitHub https://github.com/raphaelsulzer/dsr-benchmark

… survey and benchmark traditional and novel learning-based algorithms that address the problem of surface reconstruction from point clouds.

… Traditionally, different handcrafted priors of the input points or the output surface have been proposed to make the problem more tractable.

… In contrast to traditional approaches, deep surface reconstruction methods can learn priors directly from a training set of point clouds and corresponding true surfaces.

In … survey, … detail how different handcrafted and learned priors affect the robustness of methods to defect-laden input and their capability to generate geometric and topologically accurate reconstructions.

In … benchmark, … evaluate the reconstructions of several traditional and learning-based methods on the same grounds.

… show that learning-based methods can generalize to unseen shape categories, but their training and test sets must share the same point cloud characteristics.

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