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No existing spherical convolutional neural network (CNN) framework is both computationally scalable and rotationally equivariant.
Spherical CNNs on unstructured grids
C. M. Jiang, J. Huang, K. Kashinath, P., P. Marcus, and M. Niessner · 1901
Earlier work this paper cites.
Gauge equivariant convolutional networks and the icosahedral CNN
T. S. Cohen, M. Weiler, B. Kicanaoglu, and M. Welling · 1902
Earlier work this paper cites.
Orientation-aware semantic segmentation on icosahedron spheres
C. Zhang, S. Liwicki, W. Smith, and R. Cipolla · 1907
Earlier work this paper cites.
Tangent images for mitigating spherical distortion
M. Eder, M. Shvets, J. Lim, and J. Frahm · 1912
Earlier work this paper cites.
Computing Fourier transforms and convolutions on the sphere
J. R. Driscoll and D. M. Jr. Healy · 1994
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Theoretical aspects of group equivariant neural networks
C. Esteves · 2004
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C. Esteves, A. Makadia, and K. Daniilidis · 2006
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FFTs on the rotation group
P. Kostelec and D. Rockmore · 2008
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Efficient generalized spherical CNNs
O. J. Cobb, C. G. R. Wallis, A. N. Mavor-Parker, A. Marignier, M.A. Price, M. d’Avezac, and Jason McEwen · 2010
Earlier work this paper cites.
Harmonic analysis of spherical sampling in diffusion MRI
A. Daducci, J. D. McEwen, D. Van De Ville, J. Ph. Thiran, and Y. Wiaux · 2011
Earlier work this paper cites.
A novel sampling theorem on the sphere
J. D. McEwen and Y. Wiaux · 2011
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Cubature formulas and discrete Fourier transform on compact manifolds
I. Z. Pesenson and D. Geller · 2011
Earlier work this paper cites.
Hohonet: 360 indoor holistic understanding with latent horizontal features
C. Sun, M. Sun, and H. Chen · 2011
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Simple copy-paste is a strong data augmentation method for instance segmentation
G. Ghiasi, Y. Cui, A. Srinivas, R. Qian, T. Lin, E. D. Cubuk, Q. V. Le, and B. Zoph · 2012
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On the computation of directional scale-discretized wavelet transforms on the sphere
J. D. McEwen, P. Vandergheynst, and Y. Wiaux · 2013
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ADAM: A method for stochastic gradient descent
D. P. Kingma and J. L. Ba · 2015
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Xception: Deep learning with depthwise separable convolutions
F. Chollet · 2017
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T. S. Cohen, M. Geiger, J. Köhler, and M. Welling · 2018
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Learning SO(3) equivariant representations with spherical CNNs
C. Esteves, C. Allen-Blanchette, A. Makadia, and K. Daniilidis · 2018
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Clebsch-Gordan nets: a fully Fourier space spherical convolutional neural network
R. Kondor, Z. Lin, and S. Trivedi · 2018
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O. Ronneberger, P. Fischer, and T. Brox · 2015
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Group equivariant convolutional networks
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A. Chang, A. Dai, T. Funkhouser, M. Halber, M. Nießner, M. Savva, S. Song, A. Zeng, and Y. Zhang · 2017
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N. Perraudin, M. Defferrard, T. Kacprzak, and R. Sgier · 2019
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Pano3D: A holistic benchmark and a solid baseline for 360° depth estimation
G. Albanis, N. Zioulis, P. Drakoulis, V. Gkitsas, V. Sterzentsenko, F. Alvarez, D. Zarpalas, and P. Daras · 2021
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Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. M. Bronstein, J. Bruna, T. Cohen, and P. Veličković · 2021
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Equivariant networks for pixelized spheres
M. Shakerinava and S. Ravanbakhsh · 2021
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Scattering networks on the sphere for scalable and rotationally equivariant spherical CNNs
J. D. McEwen, C. Wallis, and A. N. Mavor-Parker · 2022
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Möbius convolutions for spherical CNNs
T. W. Mitchel, N. Aigerman, V. G. Kim, and M. Kazhdan · 2022
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