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We present a self-supervised task on point clouds, in order to learn meaningful point-wise features that encode local structure around each point.
A computer oriented geodetic data base and a new technique in file sequencing
G. M. Morton · 1966
Earlier work this paper cites.
Fast construction of k-nearest neighbor graphs for point clouds
M. Connor and P. Kumar · 2010
Earlier work this paper cites.
Space-filling curves
H. Sagan · 2012
Earlier work this paper cites.
Spatially-sparse convolutional neural networks
B. Graham · 2014
Earlier work this paper cites.
ShapeNet: An Information-Rich 3D Model Repository
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Earlier work this paper cites.
Unsupervised visual representation learning by context prediction
C. Doersch, A. Gupta, and A. A. Efros · 2015
Earlier work this paper cites.
Sparse 3d convolutional neural networks
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Earlier work this paper cites.
Voxnet: A 3d convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
Earlier work this paper cites.
Deeppano: Deep panoramic representation for 3-d shape recognition
B. Shi, S. Bai, Z. Zhou, and X. Bai · 2015
Earlier work this paper cites.
Multi-view convolutional neural networks for 3d shape recognition
H. Su, S. Maji, E. Kalogerakis, and E. Learned-Miller · 2015
Earlier work this paper cites.
Anticipating the future by watching unlabeled video
C. Vondrick, H. Pirsiavash, and A. Torralba · 2015
Earlier work this paper cites.
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
Earlier work this paper cites.
Discriminative unsupervised feature learning with exemplar convolutional neural networks
A. Dosovitskiy, P. Fischer, J. T. Springenberg, M. Riedmiller, and T. Brox · 2016
Earlier work this paper cites.
Point cloud labeling using 3d convolutional neural network
J. Huang and S. You · 2016
Earlier work this paper cites.
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
Cited alongside, same era.
A scalable active framework for region annotation in 3d shape collections
L. Yi, V. G. Kim, D. Ceylan, I.-C. Shen, M. Yan, H. Su, C. Lu, Q. Huang, A. Sheffer, and L. Guibas · 2016
Cited alongside, same era.
R. Zhang, P. Isola, and A. A. Efros · 2016
Cited alongside, same era.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
A. Dai, A. X. Chang, M. Savva, M. Halber, T. A. Funkhouser, and M. Nießner · 2017
Cited alongside, same era.
Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks
M. Engelcke, D. Rao, D. Z. Wang, C. H. Tong, and I. Posner · 2017
Cited alongside, same era.
Learning shape abstractions by assembling volumetric primitives
S. Tulsiani, H. Su, L. J. Guibas, A. A. Efros, and J. Malik · 2017
Later among the works it cites.
Large-scale 3d shape reconstruction and segmentation from shapenet core55
L. Yi, L. Shao, M. Savva, H. Huang, Y. Zhou, Q. Wang, B. Graham, M. Engelcke, R. Klokov, V. Lempitsky, et al · 2017
Later among the works it cites.
Syncspeccnn: Synchronized spectral cnn for 3d shape segmentation
L. Yi, H. Su, X. Guo, and L. J. Guibas · 2017
Later among the works it cites.
Weisfeiler-lehman neural machine for link prediction
M. Zhang and Y. Chen · 2017
Later among the works it cites.
Exploring spatial context for 3d semantic segmentation of point clouds
F. Engelmann, T. Kontogianni, A. Hermans, and B. Leibe · 2018
Later among the works it cites.
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Snapnet-r: Consistent 3d multi-view semantic labeling for robotics
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Inductive representation learning on large graphs
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Escape from cells: Deep kd-networks for the recognition of 3d point cloud models
R. Klokov and V. Lempitsky · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
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Octnet: Learning deep 3d representations at high resolutions
G. Riegler, A. O. Ulusoy, and A. Geiger · 2017
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Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
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S. Gidaris, P. Singh, and N. Komodakis · 2018
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Recurrent slice networks for 3d segmentation of point clouds
Q. Huang, W. Wang, and U. Neumann · 2018
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Large-scale point cloud semantic segmentation with superpoint graphs
L. Landrieu and M. Simonovsky · 2018
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Tangent convolutions for dense prediction in 3d
M. Tatarchenko, J. Park, V. Koltun, and Q.-Y. Zhou · 2018
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Tracking emerges by colorizing videos
C. Vondrick, A. Shrivastava, A. Fathi, S. Guadarrama, and K. Murphy · 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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3d recurrent neural networks with context fusion for point cloud semantic segmentation
X. Ye, J. Li, H. Huang, L. Du, and X. Zhang · 2018
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Dynamic graph cnn for learning on point clouds
Z. L. S. E. S. M. M. B. J. M. S. Yue Wang, Yongbin Sun · 2018
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