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Recent state-of-the-art methods for point cloud processing are based on the notion of point convolution, for which several approaches have been proposed.
The graph neural network model
F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini · 2008
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Flexible, high performance convolutional neural networks for image classification
D. C. Cireşan, U. Meier, J. Masci, L. M. Gambardella, and J. Schmidhuber · 2011
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ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Spectral networks and locally connected networks on graphs
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun · 2014
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Spatially-sparse convolutional neural networks
B. Graham · 2014
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Learning rich features from RGB-D images for object detection and segmentation
S. Gupta, R. Girshick, P. Arbeláez, and J. Malik · 2014
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Mind the gap: modeling local and global context in (road) networks
J. A. Montoya-Zegarra, J. D. Wegner, L. Ladickỳ, and K. Schindler · 2014
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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VoxNet: A 3D convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
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U-Net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
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Multi-view convolutional neural networks for 3D shape recognition
H. Su, S. Maji, E. Kalogerakis, and E. Learned-Miller · 2015
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3D ShapeNets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
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3D semantic parsing of large-scale indoor spaces
I. Armeni, O. Sener, A. R. Zamir, H. Jiang, I. Brilakis, M. Fischer, and S. Savarese · 2016
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Convolutional neural networks on graphs with fast localized spectral filtering
M. Defferrard, X. Bresson, and P. Vandergheynst · 2016
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Fast semantic segmentation of 3D point clouds with strongly varying density
T. Hackel, J. D. Wegner, and K. Schindler · 2016
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Gated graph sequence neural networks
Y. Li, D. Tarlow, M. Brockschmidt, and R. Zemel · 2016
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Volumetric and multi-view CNNs for object classification on 3D data
C. R. Qi, H. Su, M. Nießner, A. Dai, M. Yan, and L. J. Guibas · 2016
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A scalable active framework for region annotation in 3D shape collections
L. Yi, V. G. Kim, D. Ceylan, I. Shen, M. Yan, H. Su, C. Lu, Q. Huang, A. Sheffer, L. Guibas, et al · 2016
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Geometric deep learning: going beyond euclidean data
M. M. Bronstein, J. Bruna, Y. LeCun, A. Szlam, and P. Vandergheynst · 2017
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Neural message passing for quantum chemistry
J. Gilmer, S. S. Schoenholz, P. F. Riley, O. Vinyals, and G. E. Dahl · 2017
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Semantic3D.net: A new large-scale point cloud classification benchmark
T. Hackel, N. Savinov, L. Ladicky, J. D. Wegner, K. Schindler, and M. Pollefeys · 2017
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
T. N. Kipf and M. Welling · 2017
Cited alongside, same era.
Deep projective 3D semantic segmentation
F. J. Lawin, M. Danelljan, P. Tosteberg, G. Bhat, F. S. Khan, and M. Felsberg · 2017
Cited alongside, same era.
PointNet: Deep learning on point sets for 3D classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
Cited alongside, same era.
PointNet++: Deep hierarchical feature learning on point sets in a metric space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
Cited alongside, same era.
3D graph neural networks for RGDB semantic segmentation
X. Qi, R. Liao, J. Jia, S. Fidler, and R. Urtasun · 2017
Semantic classification of 3D point clouds with multiscale spherical neighborhoods
H. Thomas, F. Goulette, J.-E. Deschaud, and B. Marcotegui · 2018
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Local spectral graph convolution for point set feature learning
C. Wang, B. Samari, and K. Siddiqi · 2018
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Deep parametric continuous convolutional neural networks
S. Wang, S. Suo, W.-C. Ma, A. Pokrovsky, and R. Urtasun · 2018
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SGPN: Similarity group proposal network for 3D point cloud instance segmentation
W. Wang, R. Yu, Q. Huang, and U. Neumann · 2018
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SpiderCNN: Deep learning on point sets with parameterized convolutional filters
Y. Xu, T. Fan, M. Xu, L. Zeng, and Y. Qiao · 2018
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VoxelNet: End-to-end learning for point cloud based 3D object detection
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Cited alongside, same era.
OctNet: Learning deep 3D representations at high resolutions
G. Riegler, A. Osman Ulusoy, and A. Geiger · 2017
Cited alongside, same era.
Point convolutional neural networks by extension operators
M. Atzmon, H. Maron, and Y. Lipman · 2018
Cited alongside, same era.
SnapNet: 3D point cloud semantic labeling with 2D deep segmentation networks
A. Boulch, J. Guerry, B. Le Saux, and N. Audebert · 2018
Cited alongside, same era.
3D semantic segmentation with submanifold sparse convolutional networks
B. Graham, M. Engelcke, and L. van der Maaten · 2018
Cited alongside, same era.
Pointwise convolutional neural networks
B.-S. Hua, M.-K. Tran, and S.-K. Yeung · 2018
Cited alongside, same era.
Recurrent slice networks for 3D segmentation of point clouds
Q. Huang, W. Wang, and U. Neumann · 2018
Cited alongside, same era.
Y. Zhou and O. Tuzel · 2018
Later among the works it cites.
Edge-convolution point net for semantic segmentation of large-scale point clouds
J. Contreras and J. Denzler · 2019
Later among the works it cites.
Hierarchical depthwise graph convolutional neural network for 3D semantic segmentation of point clouds
Z. Liang, M. Yang, L. Deng, C. Wang, and B. Wang · 2019
Later among the works it cites.
Dynamic points agglomeration for hierarchical point sets learning
J. Liu, B. Ni, C. Li, J. Yang, and Q. Tian · 2019
Later among the works it cites.
Relation-shape convolutional neural network for point cloud analysis
Y. Liu, B. Fan, S. Xiang, and C. Pan · 2019
Later among the works it cites.
Point-voxel CNN for efficient 3D deep learning
Z. Liu, H. Tang, Y. Lin, and S. Han · 2019
Later among the works it cites.
KPConv: Flexible and deformable convolution for point clouds
H. Thomas, C. R. Qi, J.-E. Deschaud, B. Marcotegui, F. Goulette, and L. J. Guibas · 2019
Later among the works it cites.
Fast point cloud registration using semantic segmentation
G. Truong, S. Z. Gilani, S. M. S. Islam, and D. Suter · 2019
Later among the works it cites.
Dynamic graph CNN for learning on point clouds
Y. Wang, Y. Sun, Z. Liu, S. E. Sarma, M. M. Bronstein, and J. M. Solomon · 2019
Later among the works it cites.
PointConv: Deep convolutional networks on 3D point clouds
W. Wu, Z. Qi, and L. Fuxin · 2019
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Modeling point clouds with self-attention and Gumbel subset sampling
J. Yang, Q. Zhang, B. Ni, L. Li, J. Liu, M. Zhou, and Q. Tian · 2019
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ShellNet: Efficient point cloud convolutional neural networks using concentric shells statistics
Z. Zhang, B.-S. Hua, and S.-K. Yeung · 2019
Later among the works it cites.
PointWeb: Enhancing local neighborhood features for point cloud processing
H. Zhao, L. Jiang, C.-W. Fu, and J. Jia · 2019
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ConvPoint: Continuous convolutions for point cloud processing
A. Boulch · 2020
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Global context reasoning for semantic segmentation of 3D point clouds
Y. Ma, Y. Guo, H. Liu, Y. Lei, and G. Wen · 2020
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