30 citations · 52 across the 22 of their papers we have counts for
7 papers · 1 filter
A Hypertoroidal Covering for Perfect Color Equivariance
Yulong Yang, Zhikun Xu, Yaojun Li +1
When the color distribution of input images changes at inference, the performance of conventional neural network architectures drops considerably. A few researchers have begun to i…
Learning Color Equivariant Representations
Yulong Yang, Felix O'Mahony, Christine Allen-Blanchette
In this paper, we introduce group convolutional neural networks (GCNNs) equivariant to color variation. GCNNs have been designed for a variety of geometric transformations from 2D…
Learning to Predict 3D Rotational Dynamics from Images of a Rigid Body with Unknown Mass Distribution
Justice Mason, Christine Allen-Blanchette, Nicholas Zolman +2
In many real-world settings, image observations of freely rotating 3D rigid bodies may be available when low-dimensional measurements are not. However, the high-dimensionality of i…
Learning Interpretable Dynamics from Images of a Freely Rotating 3D Rigid Body
Justice Mason, Christine Allen-Blanchette, Nicholas Zolman +2
In many real-world settings, image observations of freely rotating 3D rigid bodies, such as satellites, may be available when low-dimensional measurements are not. However, the hig…
Equivariant Multi-View Networks
Carlos Esteves, Yinshuang Xu, Christine Allen-Blanchette +1
Several popular approaches to 3D vision tasks process multiple views of the input independently with deep neural networks pre-trained on natural images, achieving view permutation…
Learning SO(3) Equivariant Representations with Spherical CNNs
Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia +1
We address the problem of 3D rotation equivariance in convolutional neural networks. 3D rotations have been a challenging nuisance in 3D classification tasks requiring higher capac…
Polar Transformer Networks
Carlos Esteves, Christine Allen-Blanchette, Xiaowei Zhou +1
Convolutional neural networks (CNNs) are inherently equivariant to translation. Efforts to embed other forms of equivariance have concentrated solely on rotation. We expand the not…