Fetching the paper…
Reading the bibliography…
We propose an octree guided neural network architecture and spherical convolutional kernel for machine learning from arbitrary 3D point clouds.
Multidimensional binary search trees used for associative searching
J. L. Bentley · 1975
Earlier work this paper cites.
Geometric modeling using octree encoding
D. Meagher · 1982
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
Recognizing objects in range data using regional point descriptors
A. Frome, D. Huber, R. Kolluri, T. Bülow, and J. Malik · 2004
Earlier work this paper cites.
Rectified linear units improve restricted boltzmann machines
V. Nair and G. E. Hinton · 2010
Earlier work this paper cites.
Unique shape context for 3D data description
F. Tombari, S. Salti, and L. Di Stefano · 2010
Earlier work this paper cites.
Unique signatures of histograms for local surface description
F. Tombari, S. Salti, and L. Di Stefano · 2010
Earlier work this paper cites.
Spectral networks and locally connected networks on graphs
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun · 2014
Earlier work this paper cites.
Learning where to classify in multi-view semantic segmentation
H. Riemenschneider, A. Bódis-Szomorú, J. Weissenberg, and L. Van Gool · 2014
Earlier work this paper cites.
ShapeNet: An information-rich 3D model repository
A. X. Chang, T. Funkhouser, L. Guibas, P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, et al · 2015
Earlier work this paper cites.
Spatial transformer networks
M. Jaderberg, K. Simonyan, A. Zisserman, et al · 2015
Earlier work this paper cites.
Sparse convolutional neural networks
B. Liu, M. Wang, H. Foroosh, M. Tappen, and M. Pensky · 2015
Earlier work this paper cites.
3D all the way: Semantic segmentation of urban scenes from start to end in 3D
A. Martinovic, J. Knopp, H. Riemenschneider, and L. Van Gool · 2015
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.
Matconvnet: Convolutional neural networks for matlab
A. Vedaldi and K. Lenc · 2015
Earlier work this paper cites.
3D ShapeNets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
Cited alongside, same era.
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
Cited alongside, same era.
Dynamic filter networks
B. De Brabandere, X. Jia, T. Tuytelaars, and L. Van Gool · 2016
Cited alongside, same era.
Convolutional neural networks on graphs with fast localized spectral filtering
M. Defferrard, X. Bresson, and P. Vandergheynst · 2016
Cited alongside, same era.
Point cloud labeling using 3D convolutional neural network
J. Huang and S. You · 2016
Cited alongside, same era.
FPNN: Field probing neural networks for 3D data
Y. Li, S. Pirk, H. Su, C. R. Qi, and L. J. Guibas · 2016
Cited alongside, same era.
OctNet: Learning deep 3d representations at high resolutions
G. Riegler, A. Osman Ulusoy, and A. Geiger · 2017
Later among the works it cites.
Orientation-boosted voxel nets for 3D object recognition
N. Sedaghat, M. Zolfaghari, and T. Brox · 2017
Later among the works it cites.
Dynamic edge-conditioned filters in convolutional neural networks on graphs
M. Simonovsky and N. Komodakis · 2017
Later among the works it cites.
O-CNN: Octree-based convolutional neural networks for 3D shape analysis
P.-S. Wang, Y. Liu, Y.-X. Guo, C.-Y. Sun, and X. Tong · 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.
3DMatch: Learning local geometric descriptors from RGB-D reconstructions
A. Zeng, S. Song, M. Nießner, M. Fisher, J. Xiao, and T. Funkhouser · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A scalable active framework for region annotation in 3D shape collections
L. Yi, V. G. Kim, D. Ceylan, I. Shen, M. Yan, H. Su, A. Lu, Q. Huang, A. Sheffer, L. Guibas, et al · 2016
Cited alongside, same era.
Vote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks
M. Engelcke, D. Rao, D. Zeng Wang, C. Hay Tong, and I. Posner · 2017
Cited alongside, same era.
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.
Escape from cells: Deep kd-networks for the recognition of 3d point cloud models
R. Klokov and V. Lempitsky · 2017
Cited alongside, same era.
SCNN: An accelerator for compressed-sparse convolutional neural networks
A. Parashar, M. Rhu, A. Mukkara, A. Puglielli, R. Venkatesan, B. Khailany, J. Emer, S. W. Keckler, and W. J. Dally · 2017
Cited alongside, same era.
Later among the works it cites.
Deepcontext: Context-encoding neural pathways for 3D holistic scene understanding
Y. Zhang, M. Bai, P. Kohli, S. Izadi, and J. Xiao · 2017
Later among the works it cites.
Spherical cnns
T. S. Cohen, M. Geiger, J. Köhler, and M. Welling · 2018
Later among the works it cites.
Efficient 2D and 3D facade segmentation using auto-context
R. Gadde, V. Jampani, R. Marlet, and P. V. Gehler · 2018
Later among the works it cites.
3D semantic segmentation with submanifold sparse convolutional networks
B. Graham, M. Engelcke, and L. van der Maaten · 2018
Later among the works it cites.
So-net: Self-organizing network for point cloud analysis
J. Li, B. M. Chen, and G. H. Lee · 2018
Later among the works it cites.
Pointcnn
Y. Li, R. Bu, M. Sun, and B. Chen · 2018
Later among the works it cites.
Mining point cloud local structures by kernel correlation and graph pooling
Y. Shen, C. Feng, Y. Yang, and D. Tian · 2018
Later among the works it cites.
SGPN: Similarity group proposal network for 3D point cloud instance segmentation
W. Wang, R. Yu, Q. Huang, and U. Neumann · 2018
Later among the works it cites.