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Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods

Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods

31 October 2019
Luca Della Libera
Vladimir Golkov
Yue Zhu
Arman Mielke
Daniel Cremers
    3DH
    3DPC
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Papers citing "Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods"

4 / 4 papers shown
Title
PreCM: The Padding-based Rotation Equivariant Convolution Mode for Semantic Segmentation
PreCM: The Padding-based Rotation Equivariant Convolution Mode for Semantic Segmentation
Xinyu Xu
Huazhen Liu
Huilin Xiong
W. Yu
Tao Zhang
57
0
0
03 Nov 2024
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric
  graphs
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
P. D. Haan
Maurice Weiler
Taco S. Cohen
Max Welling
102
127
0
11 Mar 2020
A General Theory of Equivariant CNNs on Homogeneous Spaces
A General Theory of Equivariant CNNs on Homogeneous Spaces
Taco S. Cohen
Mario Geiger
Maurice Weiler
MLT
AI4CE
165
308
0
05 Nov 2018
Relative Camera Pose Estimation Using Convolutional Neural Networks
Relative Camera Pose Estimation Using Convolutional Neural Networks
Iaroslav Melekhov
Juha Ylioinas
Juho Kannala
Esa Rahtu
59
197
0
05 Feb 2017
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