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SE3CNN

The group SE(3) is the group of 3 dimensional rotations and translations. This library aims to create SE(3) equivariant convolutional neural networks.

Example

import torch
from se3cnn import SE3Convolution

size = 32  # space size

scalar_field = torch.randn(1, 1, size, size, size)  # [batch, _, x, y, z]

Rs_in = [(1, 0)]  # 1 scalar field
Rs_out = [(1, 1)]  # 1 vector field
conv = SE3Convolution(Rs_in, Rs_out, size=5)
# conv.weight.size() == [2] (2 radial degrees of freedom)

vector_field = conv(scalar_field)  # [batch, vector component, x, y, z]

# vector_field.size() == [1, 3, 28, 28, 28]

Hierarchy

Dependencies

Usage

Install with

python setup.py install