Scaling Spherical CNNs

Understand

Spherical CNNs generalize CNNs to functions on the sphere, by using spherical convolutions as the main linear operation.

• The most accurate and efficient way to compute spherical convolutions is in the spectral domain (via the convolution theorem), which is still costlier than the usual planar convolutions.
• For this reason, applications of spherical CNNs have so far been limited to small problems that can be approached with low model capacity.
• In this work, we show how spherical CNNs can be scaled for much larger problems.