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Diffusion models have been popular for point cloud generation tasks.
An empirical bayes approach to statistics
Herbert E Robbins · 1992
Earlier work this paper cites.
A review of point cloud registration algorithms for mobile robotics
François Pomerleau, Francis Colas, Roland Siegwart, et al · 2015
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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.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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A lidar point cloud generator: from a virtual world to autonomous driving
Xiangyu Yue, Bichen Wu, Sanjit A Seshia, Kurt Keutzer, and Alberto L Sangiovanni-Vincentelli · 2018
Earlier work this paper cites.
Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabas Poczos, and Ruslan Salakhutdinov · 2018
Earlier work this paper cites.
Learning localized generative models for 3d point clouds via graph convolution
Diego Valsesia, Giulia Fracastoro, and Enrico Magli · 2018
Earlier work this paper cites.
Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2018
Earlier work this paper cites.
Interpolated convolutional networks for 3d point cloud understanding
Jiageng Mao, Xiaogang Wang, and Hongsheng Li · 2019
Earlier work this paper cites.
Pointweb: Enhancing local neighborhood features for point cloud processing
Hengshuang Zhao, Li Jiang, Chi-Wing Fu, and Jiaya Jia · 2019
Earlier work this paper cites.
Pointflow: 3d point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 2019
Earlier work this paper cites.
3d point cloud generative adversarial network based on tree structured graph convolutions
Dong Wook Shu, Sung Woo Park, and Junseok Kwon · 2019
Cited alongside, same era.
3d point cloud denoising using graph laplacian regularization of a low dimensional manifold model
Jin Zeng, Gene Cheung, Michael Ng, Jiahao Pang, and Cheng Yang · 2019
Cited alongside, same era.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Randla-net: Efficient semantic segmentation of large-scale point clouds
Qingyong Hu, Bo Yang, Linhai Xie, Stefano Rosa, Yulan Guo, Zhihua Wang, Niki Trigoni, and Andrew Markham · 2020
Cited alongside, same era.
Deep learning for 3d point clouds: A survey
Yulan Guo, Hanyun Wang, Qingyong Hu, Hao Liu, Li Liu, and Mohammed Bennamoun · 2020
Cited alongside, same era.
Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Diffusion probabilistic models for 3d point cloud generation
Shitong Luo and Wei Hu · 2021
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3d shape generation and completion through point-voxel diffusion
Linqi Zhou, Yilun Du, and Jiajun Wu · 2021
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Noise2score: tweedie’s approach to self-supervised image denoising without clean images
Kwanyoung Kim and Jong Chul Ye · 2021
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Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz · 2021
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Pointclip: Point cloud understanding by clip
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Saining Xie, Jiatao Gu, Demi Guo, Charles R Qi, Leonidas Guibas, and Or Litany · 2020
Cited alongside, same era.
Curvanet: Geometric deep learning based on directional curvature for 3d shape analysis
Wenchong He, Zhe Jiang, Chengming Zhang, and Arpan Man Sainju · 2020
Cited alongside, same era.
Learning gradient fields for shape generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, and Bharath Hariharan · 2020
Cited alongside, same era.
Pointgrow: Autoregressively learned point cloud generation with self-attention
Yongbin Sun, Yue Wang, Ziwei Liu, Joshua Siegel, and Sanjay Sarma · 2020
Cited alongside, same era.
Softflow: Probabilistic framework for normalizing flow on manifolds
Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang, Joun Yeop Lee, and Nam Soo Kim · 2020
Cited alongside, same era.
Renrui Zhang, Ziyu Guo, Wei Zhang, Kunchang Li, Xupeng Miao, Bin Cui, Yu Qiao, Peng Gao, and Hongsheng Li · 2022
Later among the works it cites.
Sqn: Weakly-supervised semantic segmentation of large-scale 3d point clouds
Qingyong Hu, Bo Yang, Guangchi Fang, Yulan Guo, Aleš Leonardis, Niki Trigoni, and Andrew Markham · 2022
Later among the works it cites.
Nvdiff: Graph generation through the diffusion of node vectors
Xiaohui Chen, Yukun Li, Aonan Zhang, and Li-ping Liu · 2022
Later among the works it cites.
A hierarchical spatial transformer for massive point samples in continuous space
Wenchong He, Zhe Jiang, Tingsong Xiao, Zelin Xu, Shigang Chen, Ronald Fick, Miles Medina, and Christine Angelini · 2023
Later among the works it cites.
Wenchong He and Zhe Jiang · 2023
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