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We present a simple, flexible, and general framework titled Partial Registration Network (PRNet), for partial-to-partial point cloud registration.
A method for registration of 3-d shapes
Paul J. Besl and Neil D. McKay · 1992
Earlier work this paper cites.
Zippered polygon meshes from range images
Greg Turk and Marc Levoy · 1994
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Efficient variants of the ICP algorithm
Szymon Rusinkiewicz and Marc Levoy · 2001
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Robust registration of 2D and 3D point sets
Andrew W. Fitzgibbon · 2001
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Probabilistic matching for 3d scan registration
Dirk Hähnel and Wolfram Burgard · 2002
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Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching
Alexander M Bronstein, Michael Bronstein, and Ron Kimmel · 2006
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Non-rigid registration under isometric deformations
Qi-Xing Huang, Bart Adams, Martin Wicke, and Leonidas J. Guibas · 2008
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Generalized-ICP
Aleksandr Segal, Dirk Hähnel, and Sebastian Thrun · 2009
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Möbius voting for surface correspondence
Yaron Lipman and Thomas Funkhouser · 2009
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Blended intrinsic maps
Vladimir G. Kim, Yaron Lipman, and Thomas Funkhouser · 2011
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Soft maps between surfaces
Justin Solomon, Andy Nguyen, Adrian Butscher, Mirela Ben-Chen, and Leonidas Guibas · 2012
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Functional maps: A flexible representation of maps between shapes
Maks Ovsjanikov, Mirela Ben-Chen, Justin Solomon, Adrian Butscher, and Leonidas Guibas · 2012
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Sparse iterative closest point
Sofien Bouaziz, Andrea Tagliasacchi, and Mark Pauly · 2013
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Dirichlet energy for analysis and synthesis of soft maps
Justin Solomon, Leonidas Guibas, and Adrian Butscher · 2013
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Estimating or propagating gradients through stochastic neurons
Yoshua Bengio · 2013
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A review of point cloud registration algorithms for mobile robotics
François Pomerleau, Francis Colas, and Roland Siegwart · 2015
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alan Aspuru-Guzik, and Ryan P Adams · 2015
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3d ShapeNets: A deep representation for volumetric shape modeling
Zhirong Wu, Shuran Song, Aditya Khosla, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Voxnet: A 3d convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
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Multi-view convolutional neural networks for 3d shape recognition
Hang Su, Subhransu Maji, Evangelos Kalogerakis, and Erik G. Learned-Miller · 2015
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ShapeNet: An information-rich 3d model repository
Angel Xuan Chang, Thomas A. Funkhouser, Leonidas J. Guibas, Pat Hanrahan, Qi-Xing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
Earlier work this paper cites.
Point clouds registration with probabilistic data association
Gabriel Agamennoni, Simone Fontana, Roland Y. Siegwart, and Domenico G. Sorrenti · 2016
Earlier work this paper cites.
Collaborative 3d reconstruction using heterogeneous UAVs: System and experiments
Timo Hinzmann, Thomas Stastny, Gianpaolo Conte, Patrick Doherty, Piotr Rudol, Marius Wzorek, Enric Galceran, Roland Siegwart, and Igor Gilitschenski · 2016
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Go-ICP: A globally optimal solution to 3d ICP point-set registration
Jiaolong Yang, Hongdong Li, Dylan Campbell, and Yunde Jia · 2016
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SE-Sync: A certifiably correct algorithm for synchronization over the Special Euclidean group
David M. Rosen, Luca Carlone, Afonso S. Bandeira, and John J. Leonard · 2016
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Point registration via efficient convex relaxation
Haggai Maron, Nadav Dym, Itay Kezurer, Shahar Kovalsky, and Yaron Lipman · 2016
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Entropic metric alignment for correspondence problems
Justin Solomon, Gabriel Peyré, Vladimir G. Kim, and Suvrit Sra · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Learning aligned cross-modal representations from weakly aligned data
Lluis Castrejon, Yusuf Aytar, Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
Learning SO(3) equivariant representations with spherical CNNs
Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia, and Kostas Daniilidis · 2017
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PointCNN: Convolution on X-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
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Point convolutional neural networks by extension operators
Matan Atzmon, Haggai Maron, and Yaron Lipman · 2018
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SPLATNet: Sparse lattice networks for point cloud processing
Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, and Jan Kautz · 2018
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SplineCNN: Fast geometric deep learning with continuous B-spline kernels
Matthias Fey, Jan Eric Lenssen, Frank Weichert, and Heinrich Müller · 2018
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Discovery of latent 3d keypoints via end-to-end geometric reasoning
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Yusuf Aytar, Lluis Castrejon, Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
Cited alongside, same era.
Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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Connecting generative adversarial networks and actor-critic methods
David Pfau and Oriol Vinyals · 2016
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Fast global registration
Qian-Yi Zhou, Jaesik Park, and Vladlen Koltun · 2016
Cited alongside, same era.
Volumetric and multi-view CNNs for object classification on 3d data
Charles Ruizhongtai Qi, Hao Su, Matthias Nießner, Angela Dai, Mengyuan Yan, and Leonidas Guibas · 2016
Cited alongside, same era.
Categorical reparameterization with Gumbel-Softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2017
Cited alongside, same era.
Supasorn Suwajanakorn, Noah Snavely, Jonathan J Tompson, and Mohammad Norouzi · 2018
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Deep part induction from articulated object pairs
Li Yi, Haibin Huang, Difan Liu, Evangelos Kalogerakis, Hao Su, and Leonidas Guibas · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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The sound of pixels
Hang Zhao, Chuang Gan, Andrew Rouditchenko, Carl Vondrick, Josh McDermott, and Antonio Torralba · 2018
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Audio-visual scene analysis with self-supervised multisensory features
Andrew Oweppns and Alexei A Efros · 2018
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Looking to listen at the cocktail party: A speaker-independent audio-visual model for speech separation
Ariel Ephrat, Inbar Mosseri, Oran Lang, Tali Dekel, Kevin Wilson, Avinatan Hassidim, William T. Freeman, and Michael Rubinstein · 2018
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RotationNet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints
Asako Kanezaki, Yasuyuki Matsushita, and Yoshifumi Nishida · 2018
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Learning latent permutations with Gumbel–Sinkhorn networks
Gonzalo Mena, David Belanger, Scott Linderman, and Jasper Snoek · 2018
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PointNetLK: Robust & efficient point cloud registration using PointNet
Hunter Goforth, Yasuhiro Aoki, R. Arun Srivatsan, and Simon Lucey · 2019
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Deep closest point: Learning representations for point cloud registration
Yue Wang and Justin Solomon · 2019
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BA-net: Dense bundle adjustment networks
Chengzhou Tang and Ping Tan · 2019
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A polynomial-time solution for robust registration with extreme outlier rates
Heng Yang and Luca Carlone · 2019
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Dynamic graph CNN for learning on point clouds
Yue Wang, Yongbin Sun, Sanjay E. Sarma Ziwei Liu, Michael M. Bronstein, and Justin M. Solomon · 2019
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Learning geometric operators on meshes
Yu Wang, Vladimir Kim, Michael Bronstein, and Justin Solomon · 2019
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KPConv: Flexible and deformable convolution for point clouds
Hugues Thomas, Charles Ruizhongtai Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, Franccois Goulette, and Leonidas J. Guibas · 2019
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Reversible harmonic maps between discrete surfaces
Danielle Ezuz, Justin Solomon, and Mirela Ben-Chen · 2019
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Self-supervised learning of dense shape correspondence
Oshri Halimi, Or Litany, Emanuele Rodolà, Alex Bronstein, and Ron Kimmel · 2019
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Rethinking imagenet pre-training
Kaiming He, Ross B. Girshick, and Piotr Dollár · 2019
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