Point cloud geometry is cast as a statistical manifold of per-point Gaussians, with POLI learning the mapping self-supervisedly to improve perception without labeled data.
Make it dense: Self-supervised geometric scan comple- tion of sparse 3D lidar scans in large outdoor envi- ronments.IEEE Robotics and Automation Letters, 7 (3):8534–8541
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Learning Point Cloud Geometry as a Statistical Manifold: Theory and Practice
Point cloud geometry is cast as a statistical manifold of per-point Gaussians, with POLI learning the mapping self-supervisedly to improve perception without labeled data.