Image: Choy et al
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Extracting geometric features from 3D scans or point clouds is the first step in applications such as registration, reconstruction, and tracking.
Ranked #1 on 3D Feature Matching on 3DMatch Benchmark
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data.
Ranked #3 on 3D Object Classification on ModelNet40
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown.