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Recent advances in deep learning for 3D point clouds have shown great promises in scene understanding tasks thanks to the introduction of convolution operators to consume 3D point clouds directly in a neural network.
A volumetric method for building complex models from range images
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Scale-dependent/invariant local 3d shape descriptors for fully automatic registration of multiple sets of range images
J. Novatnack and K. Nishino · 2008
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Visualizing high-dimensional data using t-sne
L. van der Maaten and G. Hinton · 2008
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Multi-fourier spectra descriptor and augmentation with spectral clustering for 3d shape retrieval
A. Tatsuma and M. Aono · 2009
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Surface feature detection and description with applications to mesh matching
A. Zaharescu, E. Boyer, K. Varanasi, and R. Horaud · 2009
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On the repeatability and quality of keypoints for local feature-based 3d object retrieval from cluttered scenes
A. Mian, M. Bennamoun, and R. Owens · 2010
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Unique signatures of histograms for local surface description
F. Tombari, S. Salti, and L. Di Stefano · 2010
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On the repeatability of the local reference frame for partial shape matching
A. Petrelli and L. Di Stefano · 2011
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Rotational projection statistics for 3d local surface description and object recognition
Y. Guo, F. Sohel, M. Bennamoun, M. Lu, and J. Wan · 2013
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Shapenet: An information-rich 3d model repository
A. X. Chang, T. A. Funkhouser, L. J. Guibas, P. Hanrahan, Q.-X. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, J. Xiao, L. Yi, and F. Yu · 2015
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Spatial transformer networks
M. Jaderberg, K. Simonyan, A. Zisserman, and k. kavukcuoglu · 2015
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Deep learning
Y. LeCun, Y. Bengio, and G. Hinton · 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 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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Gift: A real-time and scalable 3d shape search engine
S. Bai, X. Bai, Z. Zhou, Z. Zhang, and L. Jan Latecki · 2016
Cited alongside, same era.
Deep aggregation of local 3d geometric features for 3d model retrieval
T. Furuya and R. Ohbuchi · 2016
Cited alongside, same era.
Scenenn: A scene meshes dataset with annotations
B.-S. Hua, Q.-H. Pham, D. T. Nguyen, M.-K. Tran, L.-F. Yu, and S.-K. Yeung · 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.
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.
Shrec16 track: largescale 3d shape retrieval from shapenet core55
M. Savva, F. Yu, H. Su, M. Aono, B. Chen, D. Cohen-Or, W. Deng, H. Su, S. Bai, X. Bai, et al · 2016
Recurrent slice networks for 3d segmentation on point clouds
Q. Huang, W. Wang, and U. Neumann · 2018
Later among the works it cites.
Pointcnn: Convolution on x-transformed points
Y. Li, R. Bu, M. Sun, and B. Chen · 2018
Later among the works it cites.
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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Clusternet: Deep hierarchical cluster network with rigorously rotation-invariant representation for point cloud analysis
C. Chen, G. Li, R. Xu, T. Chen, M. Wang, and L. Lin · 2019
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Equivariant multi-view networks
C. Esteves, Y. Xu, C. Allen-Blanchette, and K. Daniilidis · 2019
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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.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
A. Dai, A. X. Chang, M. Savva, M. Halber, T. Funkhouser, and M. Niessner · 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.
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.
Octnet: Learning deep 3d representations at high resolutions
G. Riegler, A. O. Ulusoy, and A. Geiger · 2017
Cited alongside, same era.
Y. Guo, H. Wang, Q. Hu, H. Liu, L. Liu, and M. Bennamoun · 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.
Effective rotation-invariant point cnn with spherical harmonics kernels
A. Poulenard, M.-J. Rakotosaona, Y. Ponty, and M. Ovsjanikov · 2019
Later among the works it cites.
Spherical fractal convolutional neural networks for point cloud recognition
Y. Rao, J. Lu, and J. Zhou · 2019
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Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data
M. A. Uy, Q.-H. Pham, B.-S. Hua, D. T. Nguyen, and S.-K. Yeung · 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.
Rotation invariant convolutions for 3d point clouds deep learning
Z. Zhang, B.-S. Hua, D. W. Rosen, and S.-K. Yeung · 2019
Later among the works it cites.
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.
Pointwise rotation-invariant network with adaptive sampling and 3d spherical voxel convolution
Y. You, Y. Lou, Q. Liu, Y.-W. Tai, L. Ma, C. Lu, and W. Wang · 2020
Closest in time.
Lrf-net: Learning local reference frames for 3d local shape description and matching
A. Zhu, J. Yang, C. Zhao, K. Xian, Z. Cao, and X. Li · 2020
Closest in time.