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Three-dimensional object recognition has recently achieved great progress thanks to the development of effective point cloud-based learning frameworks, such as PointNet and its extensions.
Radial basis functions, multi-variable functional interpolation and adaptive networks
David S Broomhead and David Lowe · 1988
Earlier work this paper cites.
Function approximation and time series prediction with neural networks
Roger D Jones, YC Lee, CW Barnes, GW Flake, K Lee, PS Lewis, and S Qian · 1990
Earlier work this paper cites.
Introduction to radial basis function networks, 1996
Mark JL Orr et al · 1996
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
Earlier work this paper cites.
Reconstruction and representation of 3d objects with radial basis functions
Jonathan C Carr, Richard K Beatson, Jon B Cherrie, Tim J Mitchell, W Richard Fright, Bruce C McCallum, and Tim R Evans · 2001
Earlier work this paper cites.
Shape distributions
Robert Osada, Thomas Funkhouser, Bernard Chazelle, and David Dobkin · 2002
Earlier work this paper cites.
Face recognition with radial basis function (rbf) neural networks
Meng Joo Er, Shiqian Wu, Juwei Lu, and Hock Lye Toh · 2002
Earlier work this paper cites.
Geodesic object representation and recognition
A Ben Hamza and Hamid Krim · 2003
Earlier work this paper cites.
Shape classification using the inner-distance
Haibin Ling and David W Jacobs · 2007
Earlier work this paper cites.
Using radial basis function networks for function approximation and classification
Yue Wu, Hui Wang, Biaobiao Zhang, and K-L Du · 2012
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Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Octnet: Learning deep 3d representations at high resolutions
Gernot Riegler, Ali Osman Ulusoy, and Andreas Geiger · 2017
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Roman Klokov and Victor Lempitsky · 2017
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Dynamic edge-conditioned filters in convolutional neural networks on graphs
Martin Simonovsky and Nikos Komodakis · 2017
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Yangyan Li, Soeren Pirk, Hao Su, Charles R Qi, and Leonidas J Guibas · 2016
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Volumetric and multi-view cnns for object classification on 3d data
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al · 2016
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Pointnet: Deep learning on point sets for 3d classification and segmentation
R Qi Charles, Hao Su, Mo Kaichun, and Leonidas J Guibas · 2017
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Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan R Salakhutdinov, and Alexander J Smola · 2017
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Radial basis function neural networks: A review
Gholam ali Montazer, Davar Giveki, Maryam Karami, and Homayon Rastegar · 2018
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Geonet: Deep geodesic networks for point cloud analysis
Tong He, Haibin Huang, Li Yi, Yuqian Zhou, Chihao Wu, Jue Wang, and Stefano Soatto · 2019
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