Feb 8, 2022 · We analyze the role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images.

In the present paper, we evaluate the performance of equiv- ariant classification and semantic segmentation models. (S2CNNs (Cohen et al., 2018)) on spherical ...

We analyze the role of rotational equivariance in CNNs applied to spherical images. We compare the performance of the group equivariant networks known as S2CNNs ...

I Use “clean” academic problems and simple networks to minimize influence of dataset and optimized architectures / training procedures ...

The role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images and the performance of the group equivariant networks ...

Sep 6, 2024 · We analyze the role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images.

This repository contains the semantic segmentation code for spherical CNNs used in Equivariance versus Augmentation for Spherical Images [1].

Jul 12, 2022 · We analyze the role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images. We compare the perfor- ...

We analyze the role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images. We compare the performance of the group ...