Fetching the paper…
Reading the bibliography…
Deep learning on point clouds has made a lot of progress recently.
Using spin images for efficient object recognition in cluttered 3d scenes
A. E. Johnson and M. Hebert · 1999
Earlier work this paper cites.
Shape context: A new descriptor for shape matching and object recognition
S. J. Belongie, J. Malik, and J. Puzicha · 2000
Earlier work this paper cites.
Aligning point cloud views using persistent feature histograms
R. B. Rusu, N. Blodow, Z. Marton, and M. Beetz · 2008
Earlier work this paper cites.
Fast point feature histograms (fpfh) for 3d registration
R. B. Rusu, N. Blodow, and M. Beetz · 2009
Earlier work this paper cites.
Multi-fourier spectra descriptor and augmentation with spectral clustering for 3d shape retrieval
A. Tatsuma and M. Aono · 2009
Earlier work this paper cites.
Unique signatures of histograms for local surface description
F. Tombari, S. Salti, and L. D. Stefano · 2010
Earlier work this paper cites.
Tutorial: Point cloud library: Three-dimensional object recognition and 6 dof pose estimation
A. Aldoma, Z. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. B. Rusu, S. Gedikli, and M. Vincze · 2012
Earlier work this paper cites.
Discrete signal processing on graphs
A. Sandryhaila and J. M. F. Moura · 2013
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.
Voxnet: A 3d convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
Earlier work this paper cites.
Multi-view convolutional neural networks for 3d shape recognition
H. Su, S. Maji, E. Kalogerakis, and E. G. Learnedmiller · 2015
Cited alongside, same era.
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.
Gift: A real-time and scalable 3d shape search engine
S. Bai, X. Bai, Z. Zhou, Z. Zhang, and L. J. Latecki · 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.
Deep aggregation of local 3d geometric features for 3d model retrieval
T. Furuya and R. Ohbuchi · 2016
Cited alongside, same era.
Volumetric and multi-view cnns for object classification on 3d data
C. R. Qi, H. Su, M. Niebner, A. Dai, M. Yan, and L. J. Guibas · 2016
Graph signal processing: Overview, challenges, and applications
A. Ortega, P. Frossard, J. Kovacevic, J. M. F. Moura, and P. Vandergheynst · 2017
Later among the works it cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 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.
Spherical cnns
T. S. Cohen, M. Geiger, J. Kohler, and M. Welling · 2018
Closest in time.
Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints
A. Kanezaki, Y. Matsushita, and Y. Nishida · 2018
Closest in time.
Rgcnn: Regularized graph cnn for point cloud segmentation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Pointnet: Deep learning on point sets for 3d classification and segmentation
R. Q. Charles, H. Su, M. Kaichun, and L. J. Guibas · 2017
Cited alongside, same era.
Fast resampling of 3d point clouds via graphs
S. Chen, D. Tian, C. Feng, A. Vetro, and J. Kovacevic · 2017
Cited alongside, same era.
Learning so(3) equivariant representations with spherical cnns
C. Esteves, C. Allenblanchette, A. Makadia, and K. Daniilidis · 2017
Cited alongside, same era.
G. Te, W. Hu, A. Zheng, and Z. Guo · 2018
Closest in time.
Tensor field networks: Rotation- and translation-equivariant neural networks for 3d point clouds
N. Thomas, T. Smidt, S. Kearnes, L. Yang, L. Li, K. Kohlhoff, and P. F. Riley · 2018
Closest in time.
Dynamic graph cnn for learning on point clouds
Y. Wang, Y. Sun, Z. Liu, S. E. Sarma, M. M. Bronstein, and J. Solomon · 2018
Closest in time.
Cubenet: Equivariance to 3d rotation and translation
D. E. Worrall and G. J. Brostow · 2018
Closest in time.