On the Fourier analysis in the SO(3) space : EquiLoPO Network

arXiv:2404.15979v1 Announce Type: cross
Abstract: Analyzing volumetric data with rotational invariance or equivariance is an active topic in current research. Existing deep-learning approaches utilize either group convolutional networks limited to discrete rotations or steerable convolutional networks with constrained filter structures. This work proposes a novel equivariant neural network architecture that achieves analytical Equivariance to Local Pattern Orientation on the continuous SO(3) group while allowing unconstrained trainable filters - EquiLoPO Network. Our key innovations are a group convolutional operation leveraging irreducible …

analysis arxiv cs.cv cs.lg fourier math.gr network space type