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Multi-level 3D CNN for Learning Multi-scale Spatial Features
[article]
2019
arXiv
pre-print
3D object recognition accuracy can be improved by learning the multi-scale spatial features from 3D spatial geometric representations of objects such as point clouds, 3D models, surfaces, and RGB-D data. Current deep learning approaches learn such features either using structured data representations (voxel grids and octrees) or from unstructured representations (graphs and point clouds). Learning features from such structured representations is limited by the restriction on resolution and tree
arXiv:1805.12254v2
fatcat:xfmichbn2jgn7gllu2uyknfkzu