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A survey of downsampling and upsampling methods for 3D Point Cloud Processing
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
Adaptive Hierarchical Down-Sampling for Point Cloud Classification
Shai Avidan: Learning to Sample
PointASNL: Robust Point Clouds Processing Using Nonlocal Neural Networks With Adaptive Sampling
Unsupervised Learning of Shape and Pose with Differentiable Point Clouds
Maximum Leverage Sampling for the selection of correspondences (synthetic point cloud)
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver (6-min video)
E20 Guocheng Qian PU GCN Point Cloud Upsampling using Graph Convolutional Networks
Mesh → Point Cloud: Uniformly Sampling Meshes by Area
Differentiable DAG Sampling
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Last Updated: August 21, 2026
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![[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver (6-min video)](https://i.ytimg.com/vi/FL8LMk_qWb4/mqdefault.jpg)
