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Point clouds provide a flexible geometric representation suitable for countless applications in computer graphics; they also comprise the raw output of most 3D data acquisition devices.
Backpropagation Applied to Handwritten ZIP Code Recognition
Yann LeCun, Bernhard Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne Hubbard, and Lawrence D Jackel. 1989 · 1989
Earlier work this paper cites.
Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
Andrew E. Johnson and Martial Hebert. 1999 · 1999
Earlier work this paper cites.
Shape Context: A New Descriptor for Shape Matching and Object Recognition. In Proc. NIPS
Serge Belongie, Jitendra Malik, and Jan Puzicha. 2001 · 2001
Earlier work this paper cites.
Integral Invariants for Shape Matching
Siddharth Manay, Daniel Cremers, Byung-Woo Hong, Anthony J Yezzi, and Stefano Soatto. 2006 · 2006
Earlier work this paper cites.
Shape Classification using the Inner-distance
Haibin Ling and David W Jacobs. 2007 · 2007
Earlier work this paper cites.
Laplace-Beltrami Eigenfunctions for Deformation Invariant Shape Representation. In Proc. SGP
Raif M Rustamov. 2007 · 2007
Earlier work this paper cites.
Towards 3D Point Cloud Based Object Maps for Household Environments
Radu Bogdan Rusu, Zoltan Csaba Marton, Nico Blodow, Mihai Dolha, and Michael Beetz. 2008b · 2008
Earlier work this paper cites.
Shape-based Recognition of 3D Point Clouds in Urban Environments. In Proc. ICCV
Aleksey Golovinskiy, Vladimir G. Kim, and Thomas Funkhouser. 2009 · 2009
Earlier work this paper cites.
Fast Point Feature Histograms (FPFH) for 3D Registration. In Proc. ICRA
Radu Bogdan Rusu, Nico Blodow, and Michael Beetz. 2009 · 2009
Earlier work this paper cites.
The Graph Neural Network Model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2009 · 2009
Earlier work this paper cites.
A Concise and Provably Informative Multi-scale Signature based on Heat Diffusion
Jian Sun, Maks Ovsjanikov, and Leonidas Guibas. 2009 · 2009
Earlier work this paper cites.
Scale-invariant Heat Kernel Signatures for Non-rigid Shape Recognition. In Proc. CVPR
Michael M Bronstein and Iasonas Kokkinos. 2010 · 2010
Earlier work this paper cites.
The Wave Kernel Signature: A Quantum Mechanical Approach to Shape Analysis. In Proc. ICCV Workshops
Mathieu Aubry, Ulrich Schlickewei, and Daniel Cremers. 2011 · 2011
Earlier work this paper cites.
A Combined Texture-shape Descriptor for Enhanced 3D Feature Matching. In Proc. ICIP
Federico Tombari, Samuele Salti, and Luigi Di Stefano. 2011 · 2011
Earlier work this paper cites.
A Survey on Shape Correspondence
Oliver Van Kaick, Hao Zhang, Ghassan Hamarneh, and Daniel Cohen-Or. 2011 · 2011
Earlier work this paper cites.
Imagenet Classification with Deep Convolutional Neural Networks. In Proc. NIPS
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
Earlier work this paper cites.
Functional Maps: A Flexible Representation of Maps between Shapes
Maks Ovsjanikov, Mirela Ben-Chen, Justin Solomon, Adrian Butscher, and Leonidas Guibas. 2012 · 2012
Earlier work this paper cites.
Spectral Networks and Locally Connected Networks on Graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun. 2013 · 2013
Earlier work this paper cites.
Auto-encoding Variational Bayes
Diederik P Kingma and Max Welling. 2013 · 2013
Earlier work this paper cites.
3D-Div: A novel Local Surface Descriptor for Feature Matching and Pairwise Range Image Registration. In Proc. ICIP
Syed Afaq Ali Shah, Mohammed Bennamoun, Farid Boussaid, and Amar A El-Sallam. 2013 · 2013
Earlier work this paper cites.
The Emerging Field of Signal Processing on Graphs: Extending High-dimensional Data Analysis to Networks and Other Irregular Domains
David I Shuman, Sunil K Narang, Pascal Frossard, Antonio Ortega, and Pierre Vandergheynst. 2013 · 2013
Earlier work this paper cites.
Generative Adversarial Nets. In Proc. NIPS
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
3D Object Recognition in Cluttered Scenes with Local Surface Features: a Survey
Yulan Guo, Mohammed Bennamoun, Ferdous Sohel, Min Lu, and Jianwei Wan. 2014 · 2014
Earlier work this paper cites.
Recognizing Objects in 3D Point Clouds with Multi-scale Local Features
Min Lu, Yulan Guo, Jun Zhang, Yanxin Ma, and Yinjie Lei. 2014 · 2014
Earlier work this paper cites.
Shapenet: An Information-rich 3D Model Repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
Cited alongside, same era.
Deep Convolutional Networks on Graph-structured Data
M. Henaff, J. Bruna, and Y. LeCun. 2015 · 2015
Cited alongside, same era.
Geodesic Convolutional Neural Networks on Riemannian Manifolds. In Proc. 3dRR
Jonathan Masci, Davide Boscaini, Michael Bronstein, and Pierre Vandergheynst. 2015 · 2015
Cited alongside, same era.
Voxnet: A 3D Convolutional Neural Network for Real-time Object Recognition. In Proc. IROS
Daniel Maturana and Sebastian Scherer. 2015 · 2015
Cited alongside, same era.
Multi-view Convolutional Neural Networks for 3D Shape Recognition. In Proc. CVPR
Hang Su, Subhransu Maji, Evangelos Kalogerakis, and Erik Learned-Miller. 2015 · 2015
Surface Networks. In Proc. CVPR
Ilya Kostrikov, Zhongshi Jiang, Daniele Panozzo, Denis Zorin, and Joan Bruna. 2017 · 2017
Later among the works it cites.
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters
Ron Levie, Federico Monti, Xavier Bresson, and Michael M Bronstein. 2017 · 2017
Later among the works it cites.
Deformable Shape Completion with Graph Convolutional Autoencoders
Or Litany, Alex Bronstein, Michael Bronstein, and Ameesh Makadia. 2017a · 2017
Later among the works it cites.
SGDR: Stochastic Gradient Descent with Warm Restarts. In International Conference on Learning Representations (ICLR) 2017 Conference Track
I. Loshchilov and F. Hutter. 2017 · 2017
Later among the works it cites.
Convolutional Neural Networks on Surfaces via Seamless Toric Covers. In Proc. SIGGRAPH
Haggai Maron, Meirav Galun, Noam Aigerman, Miri Trope, Nadav Dym, Ersin Yumer, Vladimir G Kim, and Yaron Lipman. 2017 · 2017
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Cited alongside, same era.
3D Shapenets: A Deep Representation for Volumetric Shapes. In Proc. CVPR
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao. 2015 · 2015
Cited alongside, same era.
3D Semantic Parsing of Large-Scale Indoor Spaces. In Proc. CVPR
Iro Armeni, Ozan Sener, Amir R. Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese. 2016 · 2016
Cited alongside, same era.
Recent Trends, Applications, and Perspectives in 3D Shape Similarity assessment
Silvia Biasotti, Andrea Cerri, A Bronstein, and M Bronstein. 2016 · 2016
Cited alongside, same era.
Learning Shape Correspondence with Anisotropic Convolutional Neural Networks. In Proc. NIPS
Davide Boscaini, Jonathan Masci, Emanuele Rodolà, and Michael Bronstein. 2016 · 2016
Cited alongside, same era.
Generative and Discriminative Voxel Modeling with Convolutional Neural Networks. In Proc. NIPS
Andrew Brock, Theodore Lim, James Millar Ritchie, and Nicholas J. Weston. 2016 · 2016
Cited alongside, same era.
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. In Proc. NIPS
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016 · 2016
Cited alongside, same era.
Gated graph Sequence Neural Networks. In Proc. ICLR
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel. 2016 · 2016
Cited alongside, same era.
Later among the works it cites.
Frustum PointNets for 3D Object Detection from RGB-D Data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas. 2017a · 2017
Later among the works it cites.
Neighbors Do Help: Deeply Exploiting Local Structures of Point Clouds
Yiru Shen, Chen Feng, Yaoqing Yang, and Dong Tian. 2017 · 2017
Later among the works it cites.
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs. In Proc. CVPR
Martin Simonovsky and Nikos Komodakis. 2017 · 2017
Later among the works it cites.
Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs. In Proc. ICCV
Maxim Tatarchenko, Alexey Dosovitskiy, and Thomas Brox. 2017 · 2017
Later among the works it cites.
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio. 2017 · 2017
Later among the works it cites.
Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement learning. In Proc. ICRA
Yuke Zhu, Roozbeh Mottaghi, Eric Kolve, Joseph J. Lim, Abhinav Gupta, Li Fei-Fei, and Ali Farhadi. 2017 · 2017
Later among the works it cites.
Point Convolutional Neural Networks by Extension Operators
Matan Atzmon, Haggai Maron, and Yaron Lipman. 2018 · 2018
Closest in time.
SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Matthias Fey, Jan Eric Lenssen, Frank Weichert, and Heinrich Müller. 2018 · 2018
Closest in time.
PCPNet: Learning Local Shape Properties from Raw Point Clouds
Paul Guerrero, Yanir Kleiman, Maks Ovsjanikov, and Niloy J. Mitra. 2018 · 2018
Closest in time.
Self-supervised Learning of Dense Shape Correspondence
Oshri Halimi, Or Litany, Emanuele Rodolà, Alex Bronstein, and Ron Kimmel. 2018 · 2018
Closest in time.
Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabas Poczos, and Ruslan Salakhutdinov. 2018b · 2018
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Deep Continuous Fusion for Multi-Sensor 3D Object Detection. In The European Conference on Computer Vision (ECCV)
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun. 2018 · 2018
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MotifNet: A Motif-based Graph Convolutional Network for Directed Graphs
Federico Monti, Karl Otness, and Michael M Bronstein. 2018 · 2018
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Generating 3D faces using Convolutional Mesh Autoencoders
Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, and Michael J Black. 2018 · 2018
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SPLATNet: Sparse Lattice Networks for Point Cloud Processing. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 2530–2539
Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, and Jan Kautz. 2018 · 2018
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Non-local Neural Networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He. 2018a · 2018
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Feature Denoising for Improving Adversarial Robustness
Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan Yuille, and Kaiming He. 2018 · 2018
Closest in time.
FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation. In Proc. CVPR
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian. 2018 · 2018
Closest in time.