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Point cloud upsampling (PCU) enriches the representation of raw point clouds, significantly improving the performance in downstream tasks such as classification and reconstruction.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2010
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2011
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Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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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
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Sample elimination for generating poisson disk sample sets
Cem Yuksel · 2015
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Learning efficient point cloud generation for dense 3d object reconstruction
Chen-Hsuan Lin, Chen Kong, and Simon Lucey · 2018
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Dgcnn: A convolutional neural network over large-scale labeled graphs
Anh Viet Phan, Minh Le Nguyen, Yen Lam Hoang Nguyen, and Lam Thu Bui · 2018
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Pu-net: Point cloud upsampling network
Lequan Yu, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, and Pheng-Ann Heng · 2018
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Pu-gan: a point cloud upsampling adversarial network
Ruihui Li, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, and Pheng-Ann Heng · 2019
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Point-voxel cnn for efficient 3d deep learning
Zhijian Liu, Haotian Tang, Yujun Lin, and Song Han · 2019
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Kpconv: Flexible and deformable convolution for point clouds
Hugues Thomas, Charles R Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J Guibas · 2019
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Patch-based progressive 3d point set upsampling
Wang Yifan, Shihao Wu, Hui Huang, Daniel Cohen-Or, and Olga Sorkine-Hornung · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Pugeo-net: A geometry-centric network for 3d point cloud upsampling
Yue Qian, Junhui Hou, Sam Kwong, and Ying He · 2020
Cited alongside, same era.
A novel system for off-line 3d seam extraction and path planning based on point cloud segmentation for arc welding robot
Lei Yang, Yanhong Liu, Jinzhu Peng, and Zize Liang · 2020
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Deep learning for image and point cloud fusion in autonomous driving: A review
Yaodong Cui, Ren Chen, Wenbo Chu, Long Chen, Daxin Tian, Ying Li, and Dongpu Cao · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
Predator: Registration of 3d point clouds with low overlap
Shengyu Huang, Zan Gojcic, Mikhail Usvyatsov, Andreas Wieser, and Konrad Schindler · 2021
Cited alongside, same era.
Deepi2p: Image-to-point cloud registration via deep classification
3d shape generation and completion through point-voxel diffusion
Linqi Zhou, Yilun Du, and Jiajun Wu · 2021
Later among the works it cites.
Neural points: Point cloud representation with neural fields for arbitrary upsampling
Wanquan Feng, Jin Li, Hongrui Cai, Xiaonan Luo, and Juyong Zhang · 2022
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
Later among the works it cites.
Weaklabel3d-net: A complete framework for real-scene lidar point clouds weakly supervised multi-tasks understanding
Kangcheng Liu, Yuzhi Zhao, Zhi Gao, and Ben M Chen · 2022
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Pix4point: Image pretrained transformers for 3d point cloud understanding
Guocheng Qian, Xingdi Zhang, Abdullah Hamdi, and Bernard Ghanem · 2022
Later among the works it cites.
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Jiaxin Li and Gim Hee Lee · 2021
Cited alongside, same era.
Point cloud upsampling via disentangled refinement
Ruihui Li, Xianzhi Li, Pheng-Ann Heng, and Chi-Wing Fu · 2021
Cited alongside, same era.
Pu-eva: An edge-vector based approximation solution for flexible-scale point cloud upsampling
Luqing Luo, Lulu Tang, Wanyi Zhou, Shizheng Wang, and Zhi-Xin Yang · 2021
Cited alongside, same era.
Diffusion probabilistic models for 3d point cloud generation
Shitong Luo and Wei Hu · 2021
Cited alongside, same era.
A conditional point diffusion-refinement paradigm for 3d point cloud completion
Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, and Dahua Lin · 2021
Cited alongside, same era.
Variational relational point completion network
Liang Pan, Xinyi Chen, Zhongang Cai, Junzhe Zhang, Haiyu Zhao, Shuai Yi, and Ziwei Liu · 2021
Cited alongside, same era.
Pu-gcn: Point cloud upsampling using graph convolutional networks
Guocheng Qian, Abdulellah Abualshour, Guohao Li, Ali Thabet, and Bernard Ghanem · 2021
Cited alongside, same era.
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Pointclip: Point cloud understanding by clip
Renrui Zhang, Ziyu Guo, Wei Zhang, Kunchang Li, Xupeng Miao, Bin Cui, Yu Qiao, Peng Gao, and Hongsheng Li · 2022
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Global-pbnet: A novel point cloud registration for autonomous driving
Yuchao Zheng, Yujie Li, Shuo Yang, and Huimin Lu · 2022
Later among the works it cites.
Grad-pu: Arbitrary-scale point cloud upsampling via gradient descent with learned distance functions
Yun He, Danhang Tang, Yinda Zhang, Xiangyang Xue, and Yanwei Fu · 2023
Closest in time.
Pc2: Projection-conditioned point cloud diffusion for single-image 3d reconstruction
Luke Melas-Kyriazi, Christian Rupprecht, and Andrea Vedaldi · 2023
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Dream3d: Zero-shot text-to-3d synthesis using 3d shape prior and text-to-image diffusion models
Jiale Xu, Xintao Wang, Weihao Cheng, Yan-Pei Cao, Ying Shan, Xiaohu Qie, and Shenghua Gao · 2023
Closest in time.