Steerable 3D Spherical Neurons. (arXiv:2106.13863v3 [cs.CV] UPDATED)

Web: http://arxiv.org/abs/2106.13863

Emerging from low-level vision theory, steerable filters found their
counterpart in prior work on steerable convolutional neural networks
equivariant to rigid transformations. In our work, we propose a steerable
feed-forward learning-based approach that consists of neurons with spherical
decision surfaces and operates on point clouds. Such spherical neurons are
obtained by conformal embedding of Euclidean space and have recently been
revisited in the context of learning representations of point sets. Focusing on
3D geometry, we exploit the isometry property of …

3d arxiv cv neurons