Fetching the paper…
Reading the bibliography…
We propose a self-supervised capsule architecture for 3D point clouds.
A Parallel Computation that Assigns Canonical Object-based Frames of Reference
Geoffrey F Hinton · 1981
Earlier work this paper cites.
Shape Recognition and Illusory Conjunctions
Geoffrey E Hinton and Kevin J Lang · 1985
Earlier work this paper cites.
Uniform random rotations
Ken Shoemake · 1992
Earlier work this paper cites.
Distinctive Image Features from Scale-Invariant Keypoints
David G Lowe · 2004
Earlier work this paper cites.
Pattern Recognition and Machine Learning
Christopher M Bishop · 2006
Earlier work this paper cites.
A Discriminatively Trained, Multiscale, Deformable Part Model
Pedro Felzenszwalb, David McAllester, and Deva Ramanan · 2008
Earlier work this paper cites.
Transforming Auto-Encoders
Geoffrey E Hinton, Alex Krizhevsky, and Sida D Wang · 2011
Earlier work this paper cites.
Rotation averaging
Richard Hartley, Jochen Trumpf, Yuchao Dai, and Hongdong Li · 2013
Earlier work this paper cites.
Co-hierarchical analysis of shape structures
Oliver van Kaick, Kai Xu, Hao Zhang, Yanzhen Wang, Shuyang Sun, Ariel Shamir, and Daniel Cohen-Or · 2013
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
Earlier work this paper cites.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe and Christian Szegedy · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimisation
D.P. Kingma and J. Ba · 2015
Earlier work this paper cites.
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan and Andrew Zisserman · 2015
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
You Only Look Once: Unified, Real-Time Object Detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
Earlier work this paper cites.
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision
Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, and Honglak Lee · 2016
Earlier work this paper cites.
Fast global registration
Qian-Yi Zhou, Jaesik Park, and Vladlen Koltun · 2016
Earlier work this paper cites.
A Point Set Generation Network for 3D Object Reconstruction from a Single Image
Haoqiang Fan, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Learning a Multi-View Stereo Machine
Abhishek Kar, Christian Häne, and Jitendra Malik · 2017
Earlier work this paper cites.
Pointnet: Deep Learning on Point Sets for 3D Classification and Segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Earlier work this paper cites.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Charles R Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Semantic scene completion from a single depth image
Shuran Song, Fisher Yu, Andy Zeng, Angel X Chang, Manolis Savva, and Thomas Funkhouser · 2017
Earlier work this paper cites.
Least-Squares Rigid Motion Using SVD
Olga Sorkine-Hornung and Michael Rabinovich · 2017
Cited alongside, same era.
Learning shape abstractions by assembling volumetric primitives
Shubham Tulsiani, Hao Su, Leonidas J Guibas, Alexei A Efros, and Jitendra Malik · 2017
Cited alongside, same era.
O-CNN: Octree-Based Convolutional Neural Networks for 3d Shape Analysis
Peng-Shuai Wang, Yang Liu, Yu-Xiao Guo, Chun-Yu Sun, and Xin Tong · 2017
Cited alongside, same era.
A Papier-Mâché Approach to Learning 3D Surface Generation
Thibault Groueix, Matthew Fisher, Vladimir G Kim, Bryan C Russell, and Mathieu Aubry · 2018
Cited alongside, same era.
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Arthur Jacot, Franck Gabriel, and Clément Hongler · 2018
Cited alongside, same era.
Deformable Shape Completion with Graph Convolutional Autoencoders
Or Litany, Alex Bronstein, Michael Bronstein, and Ameesh Makadia · 2018
Deep Closest Point: Learning Representations for Point Cloud Registration
Yue Wang and Justin M Solomon · 2019
Later among the works it cites.
Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2019
Later among the works it cites.
3D Point Capsule Networks
Yongheng Zhao, Tolga Birdal, Haowen Deng, and Federico Tombari · 2019
Later among the works it cites.
Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction
Rohan Chabra, Jan Eric Lenssen, Eddy Ilg, Tanner Schmidt, Julian Straub, Steven Lovegrove, and Richard Newcombe · 2020
Closest in time.
A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
Closest in time.
Bsp-net: Generating compact meshes via binary space partitioning
Zhiqin Chen, Andrea Tagliasacchi, and Hao Zhang · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Discovery of Latent 3D Keypoints via End-to-End Geometric Reasoning
Supasorn Suwajanakorn, Noah Snavely, Jonathan J Tompson, and Mohammad Norouzi · 2018
Cited alongside, same era.
Tensor Field Networks: Rotation-and Translation-Equivariant Neural Networks for 3D Point Clouds
Nathaniel Thomas, Tess Smidt, Steven Kearnes, Lusann Yang, Li Li, Kai Kohlhoff, and Patrick Riley · 2018
Cited alongside, same era.
Pixel2mesh: Generating 3d mesh models from single rgb images
Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, and Yu-Gang Jiang · 2018
Cited alongside, same era.
Adaptive o-cnn: A patch-based deep representation of 3d shapes
Peng-Shuai Wang, Chun-Yu Sun, Yang Liu, and Xin Tong · 2018
Cited alongside, same era.
Group Normalization
Yuxin Wu and Kaiming He · 2018
Cited alongside, same era.
FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
Cited alongside, same era.
Closest in time.
NASA: Neural Articulated Shape Approximation
Boyang Deng, JP Lewis, Timothy Jeruzalski, Gerard Pons-Moll, Geoffrey Hinton, Mohammad Norouzi, and Andrea Tagliasacchi · 2020
Closest in time.
Better Patch Stitching for Parametric Surface Reconstruction
Zhantao Deng, Jan Bednařík, Mathieu Salzmann, and Pascal Fua · 2020
Closest in time.
CvxNet: Learnable Convex Decomposition
Deng, Boyang and Genova, Kyle and Yazdani, Soroosh and Bouaziz, Sofien and Hinton, Geoffrey and Tagliasacchi, Andrea · 2020
Closest in time.
Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets
Clara Fernandez-Labrador, Ajad Chhatkuli, Danda Pani Paudel, Jose J Guerrero, Cédric Demonceaux, and Luc Van Gool · 2020
Closest in time.
Deep Structured Implicit Functions
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, and Thomas Funkhouser · 2020
Closest in time.
Learning multiview 3D point cloud registration
Zan Gojcic, Caifa Zhou, Jan D Wegner, Leonidas J Guibas, and Tolga Birdal · 2020
Closest in time.
Weakly-Supervised 3D Shape Completion in the Wild
Jiayuan Gu, Wei-Chiu Ma, Sivabalan Manivasagam, Wenyuan Zeng, Zihao Wang, Yuwen Xiong, Hao Su, and Raquel Urtasun · 2020
Closest in time.
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations
Davis Rempe, Tolga Birdal, Yongheng Zhao, Zan Gojcic, Srinath Sridhar, and Leonidas J. Guibas · 2020
Closest in time.
Learning to Orient Surfaces by Self-supervised Spherical CNNs
Riccardo Spezialetti, Federico Stella, Marlon Marcon, Luciano Silva, Samuele Salti, and Luigi Di Stefano · 2020
Closest in time.
ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning
Weiwei Sun, Wei Jiang, Eduard Trulls, Andrea Tagliasacchi, and Kwang Moo Yi · 2020
Closest in time.
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
Saining Xie, Jiatao Gu, Demi Guo, Charles R. Qi, Leonidas J. Guibas, and Or Litany · 2020
Closest in time.
Rpm-net: Robust point matching using learned features
Zi Jian Yew and Gim Hee Lee · 2020
Closest in time.
DeepGMR: Learning Latent Gaussian Mixture Models for Registration
Wentao Yuan, Ben Eckart, Kihwan Kim, Varun Jampani, Dieter Fox, and Jan Kautz · 2020
Closest in time.
Quaternion Equivariant Capsule Networks for 3D Point Clouds
Yongheng Zhao, Tolga Birdal, Jan Eric Lenssen, Emanuele Menegatti, Leonidas Guibas, and Federico Tombari · 2020
Closest in time.
Vector neurons: a general framework for so(3)-equivariant networks, 2021
Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacchi, and Leonidas Guibas · 2021
Closest in time.
Unsupervised part representation by flow capsules, 2021
Sara Sabour, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey E. Hinton, and David J. Fleet · 2021
Closest in time.