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FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation
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2018
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Yaoqing Yang
Chen Feng
Yiru Shen
Dong Tian
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7
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Dynamic Graph CNN for Learning on Point Clouds
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2019
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Yue Wang
Yongbin Sun
Ziwei Liu
Sanjay E. Sarma
Michael M. Bronstein
Justin Solomon
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KPConv: Flexible and Deformable Convolution for Point Clouds
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2019
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Hugues Thomas
Charles R. Qi
JeanâEmmanuel Deschaud
Beatriz Marcotegui
François Goulette
Leonidas Guibas
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6
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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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2017
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Raffaelli Charles
Hao Su
Kaichun Mo
Leonidas Guibas
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6
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PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
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2017
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Charles R. Qi
Yi Li
Hao Su
Leonidas Guibas
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3D ShapeNets: A deep representation for volumetric shapes
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2015
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Shuran Song
Aditya Khosla
Fisher Yu
Linguang Zhang
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Deep Residual Learning for Image Recognition
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2016
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Kaiming He
Xiangyu Zhang
Shaoqing Ren
Jian Sun
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SO-Net: Self-Organizing Network for Point Cloud Analysis
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2018
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Jiaxin Li
Ben M. Chen
Gim Hee Lee
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4
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PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention
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2020
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Yongbin Sun
Yue Wang
Ziwei Liu
Joshua Siegel
Sanjay E. Sarma
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3
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FlowNet3D: Learning Scene Flow in 3D Point Clouds
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2019
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Xingyu Liu
Charles R. Qi
Leonidas Guibas
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3
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PU-Net: Point Cloud Upsampling Network
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2018
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Lequan Yu
Xianzhi Li
ChiâWing Fu
Daniel CohenâOr
PhengâAnn Heng
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3
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PU-GAN: A Point Cloud Upsampling Adversarial Network
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2019
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Ruihui Li
Xianzhi Li
ChiâWing Fu
Daniel CohenâOr
PhengâAnn Heng
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3
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Escape from Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models
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2017
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Roman Klokov
Victor Lempitsky
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3
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3D-CODED: 3D Correspondences by Deep Deformation
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2018
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Thibault Groueix
Matthew Fisher
Vladimir G. Kim
Bryan Russell
Mathieu Aubry
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3
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Deep Learning for 3D Point Clouds: A Survey
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2020
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Yulan Guo
Hanyun Wang
Qingyong Hu
Hao Liu
Li Liu
Mohammed Bennamoun
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3
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Deep Closest Point: Learning Representations for Point Cloud Registration
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2019
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Yue Wang
Justin Solomon
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3
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OctNet: Learning Deep 3D Representations at High Resolutions
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2017
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Gernot Riegler
Ali Osman Ulusoy
Andreas Geiger
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3
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RPM-Net: Robust Point Matching Using Learned Features
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2020
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Zi Jian Yew
Gim Hee Lee
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2
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The Three Sigma Rule
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1994
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Friedrich Pukelsheim
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TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations
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2021
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Jiahao Pang
Duanshun Li
Dong Tian
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2
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O-CNN
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2017
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PengâShuai Wang
Yang Liu
Yuxiao Guo
Chunyu Sun
Xin Tong
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2
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CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds
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2021
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Yiming Zeng
Yue Qian
Zhiyu Zhu
Junhui Hou
Hui Yuan
Ying He
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PUGeo-Net: A Geometry-Centric Network for 3D Point Cloud Upsampling
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2020
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Yue Qian
Junhui Hou
Sam Kwong
Ying He
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2
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PointINet: Point Cloud Frame Interpolation Network
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2021
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Fan LĂź
Guang Chen
Sanqing Qu
Zhijun Li
Yinlong Liu
Alois Knoll
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2
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NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go
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2021
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Marvin Eisenberger
David NovotnĂ˝
Gael Kerchenbaum
Patrick Labatut
Natalia Neverova
Daniel Cremers
Andrea Vedaldi
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2
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SurfNet: Generating 3D Shape Surfaces Using Deep Residual Networks
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2017
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Ayan Sinha
Asim Unmesh
Qixing Huang
Karthik Ramani
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2
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Human Motion Transfer With 3D Constraints and Detail Enhancement
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2022
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Yang-Tian Sun
Qiancheng Fu
Yue-Ren Jiang
Zitao Liu
YuâKun Lai
Hongbo Fu
Lin Gao
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ConvPoint: Continuous convolutions for point cloud processing
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2020
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Alexandre Boulch
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2
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SPLATNet: Sparse Lattice Networks for Point Cloud Processing
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2018
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Hang Su
Varun Jampani
Deqing Sun
Subhransu Maji
Evangelos Kalogerakis
MingâHsuan Yang
Jan Kautz
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2
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FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis
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2018
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Nitika Verma
Edmond Boyer
Jakob Verbeek
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2
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Grid-GCN for Fast and Scalable Point Cloud Learning
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2020
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Qiangeng Xu
Xudong Sun
Cho-Ying Wu
Panqu Wang
Ulrich Neumann
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Surface Networks via General Covers
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2019
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Niv Haim
Nimrod Segol
Heli Ben-Hamu
Haggai Maron
Yaron Lipman
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MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences
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2019
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Xingyu Liu
Mengyuan Yan
Jeannette Bohg
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2
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Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence
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2020
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Abhishek Sharma
Maks Ovsjanikov
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Attention is All you Need
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Noam Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
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Relation-Shape Convolutional Neural Network for Point Cloud Analysis
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2019
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Yongcheng Liu
Bin Fan
Shiming Xiang
Chunhong Pan
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Adam: A Method for Stochastic Optimization
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Geometric Deep Learning: Going beyond Euclidean data
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Joan Bruna
Yann LeCun
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Pierre Vandergheynst
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Deep Functional Maps: Structured Prediction for Dense Shape Correspondence
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2017
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Or Litany
Tal Remez
Emanuele RodolĂ
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Learning Representations and Generative Models for 3D Point Clouds
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2017
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Olga Diamanti
Ioannis Mitliagkas
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PointConv: Deep Convolutional Networks on 3D Point Clouds
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2019
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Wenxuan Wu
Zhongang Qi
Fuxin Li
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2
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Patch-Based Progressive 3D Point Set Upsampling
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2019
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Yifan Wang
Shihao Wu
Hui Huang
Daniel CohenâOr
Olga SorkineâHornung
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Recent Trends, Applications, and Perspectives in 3D Shape Similarity Assessment
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Andrea Cerri
Alex Bronstein
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3D fully convolutional network for vehicle detection in point cloud
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2017
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Bo Li
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1
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Learning Latent Permutations with Gumbel-Sinkhorn Networks
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2018
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Gonzalo E. Mena
David Belanger
Scott W. Linderman
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VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization
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2017
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Ronald Clark
Sen Wang
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Rethinking the Inception Architecture for Computer Vision
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2016
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Christian Szegedy
Vincent Vanhoucke
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Video Frame Interpolation via Adaptive Convolution
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Simon Niklaus
Long Mai
Feng Liu
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Aggregated Residual Transformations for Deep Neural Networks
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Saining Xie
Ross Girshick
Piotr DollĂĄr
Zhuowen Tu
Kaiming He
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Geodesic Convolutional Neural Networks on Riemannian Manifolds
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2015
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Jonathan Masci
Davide Boscaini
Michael M. Bronstein
Pierre Vandergheynst
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