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Revisiting 2D Convolutional Neural Networks for Graph-based Applications

Revisiting 2D Convolutional Neural Networks for Graph-based Applications

23 May 2021
Yecheng Lyu
Xinming Huang
Ziming Zhang
    GNN
ArXivPDFHTML

Papers citing "Revisiting 2D Convolutional Neural Networks for Graph-based Applications"

5 / 5 papers shown
Title
DensePoint: Learning Densely Contextual Representation for Efficient
  Point Cloud Processing
DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing
Yongcheng Liu
Bin Fan
Gaofeng Meng
Jiwen Lu
Shiming Xiang
Chunhong Pan
3DPC
115
270
0
09 Sep 2019
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional
  Filters
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters
Yifan Xu
Tianqi Fan
Mingye Xu
Long Zeng
Yu Qiao
3DV
3DPC
150
768
0
30 Mar 2018
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
222
14,087
0
02 Dec 2016
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
234
1,811
0
25 Nov 2016
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
236
3,234
0
24 Nov 2016
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