Rotation-Invariant Autoencoders for Signals on Spheres

Type: Preprint

Publication Date: 2020-01-01

Citations: 2

DOI: https://doi.org/10.48550/arxiv.2012.04474

Locations

  • arXiv (Cornell University) - View - PDF
  • DataCite API - View

Similar Works

Action Title Year Authors
+ Rotation-Invariant Autoencoders for Signals on Spheres. 2020 Suhas Lohit
Shubhendu Trivedi
+ Learning SO(3) Equivariant Representations with Spherical CNNs 2017 Carlos Esteves
Christine Allen-Blanchette
Ameesh Makadia
Kostas Daniilidis
+ Convolutional Networks for Spherical Signals 2017 Taco Cohen
Mario Geiger
Jonas Köhler
Max Welling
+ Spherical Transformer: Adapting Spherical Signal to CNNs 2021 Yuqi Liu
Yin Wang
Haikuan Du
Shen Cai
+ Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs. 2021 Jason D. McEwen
Christopher G. R. Wallis
Augustine N. Mavor-Parker
+ Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs 2021 Jason D. McEwen
Christopher G. R. Wallis
Augustine N. Mavor-Parker
+ Learning Equivariant Representations 2020 Carlos Esteves
+ Spin-Weighted Spherical CNNs 2020 Carlos Esteves
Ameesh Makadia
Kostas Daniilidis
+ Spin-Weighted Spherical CNNs 2020 Carlos Esteves
Ameesh Makadia
Kostas Daniilidis
+ Spin-Weighted Spherical CNNs 2020 Carlos Esteves
Ameesh Makadia
Kostas Daniilidis
+ Spherical Convolutional Neural Networks: Stability to Perturbations in SO(3) 2020 Zhan Gao
Fernando Gama
Alejandro Ribeiro
+ Representation Learning on Unit Ball with 3D Roto-Translational Equivariance 2019 Sameera Ramasinghe
Salman A. Khan
Nick Barnes
Stephen Jay Gould
+ Gauge Equivariant Convolutional Networks and the Icosahedral CNN 2019 Taco Cohen
Maurice Weiler
Berkay Kicanaoglu
Max Welling
+ Spherical Transformer 2022 Sungmin Cho
Raehyuk Jung
Junseok Kwon
+ Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions 2022 Jeremy Ocampo
Matthew A. Price
Jason D. McEwen
+ PDF Chat OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression 2022 Navid Mahmoudian Bidgoli
Roberto Gerson de Albuquerque Azevedo
Thomas Maugey
Aline Roumy
Pascal Frossard
+ OSLO: On-the-Sphere Learning for Omnidirectional images and its application to 360-degree image compression 2021 Navid Mahmoudian Bidgoli
Roberto Gerson de Albuquerque Azevedo
Thomas Maugey
Aline Roumy
Pascal Frossard
+ Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods. 2019 Luca Della Libera
Vladimir Golkov
Yue Zhu
Arman Mielke
Daniel Cremers
+ Efficient Generalized Spherical CNNs 2021 Oliver Cobb
Christopher G. R. Wallis
Augustine N. Mavor-Parker
Augustin Marignier
Matthew A. Price
Mayeul d’Avezac
Jason D. McEwen
+ Spherical CNNs 2018 Taco Cohen
Mario Geiger
Jonas Koehler
Max Welling

Works Cited by This (0)

Action Title Year Authors