Point Cloud Data Augmentation is a data processing technique that enriches point cloud datasets through geometric transformations, sampling strategies, or synthetic generation to enhance model robustness and generalization in machine learning tasks.
131
Publications
9.2K
Citations
537
Authors
188
Institutions
Publications per year
2017–2026
122
Parents
Publications
131
Data augmentation: A comprehensive survey of modern approaches
Alhassan Mumuni, Fuseini Mumuni · Array · 2022 · 800 citations · Full text
Diffusion Probabilistic Models for 3D Point Cloud Generation
Shitong Luo, Wei Hu · 2021 · 566 citations
PointAugmenting: Cross-Modal Augmentation for 3D Object Detection
Chunwei Wang, Chao Ma, Ming Zhu et al. · 2021 · 449 citations
1–5 of 131
Authors
537
- CF
4
h-index
- ZL
3
h-index
- DZ
3
h-index
- SL
3
h-index
- AX
3
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1–5 of 537
Institutions
188
Chinese University of Hong Kong
Hong Kong, Hong Kong
6 h-index
16 publications
2.9K citations
Wuhan University
Wuhan, China
5 h-index
16 publications
435 citations
Zhejiang University
Hangzhou, China
5 h-index
19 publications
2K citations
Baidu (China)
Beijing, China
5 h-index
23 publications
1.7K citations
Xi'an Jiaotong University
Xi'an, China
4 h-index
8 publications
252 citations
Shanghai Jiao Tong University
Shanghai, China
4 h-index
14 publications
2K citations
Nanyang Technological University
Singapore, Singapore
4 h-index
8 publications
455 citations
Princeton University
Princeton, United States
3 h-index
8 publications
368 citations
1–8 of 188
Venues
- arXiv (Cornell University)
Repository · 22 publications · 1.4K citations
16
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- Automation in Construction
5 publications · 375 citations
5
h-index
- Sensors
4 publications · 103 citations
4
h-index
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Conference · 3 publications · 803 citations
3
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- Pattern Recognition
3 publications · 146 citations
3
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1–5