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May 10, 2022 · Artificial Intelligence

How Geometric Deep Learning Enables Spherical CNNs for Rotationally Equivariant Vision

The article explains why traditional planar CNNs fail on spherical data, describes how encoding rotational symmetry through continuous spherical representations and spherical harmonics leads to spherical convolutions that are rotation‑equivariant, and outlines the practical computation using harmonic coefficients.

Computer Visiongeometric-deep-learningrotational equivariance
0 likes · 9 min read
How Geometric Deep Learning Enables Spherical CNNs for Rotationally Equivariant Vision
Code DAO
Code DAO
May 9, 2022 · Artificial Intelligence

Hybrid Rotationally Equivariant Generalized Spherical CNNs Explained

The article introduces hybrid rotationally equivariant spherical CNNs, explains generalized signals on the sphere and rotation group, describes how linear and nonlinear operations using Clebsch‑Gordan coefficients preserve equivariance, and demonstrates efficient architectures that achieve state‑of‑the‑art results on 3D shape classification and atomic energy prediction.

3D shape classificationClebsch-Gordanatomic energy prediction
0 likes · 14 min read
Hybrid Rotationally Equivariant Generalized Spherical CNNs Explained