Point Cloud Sampling
Point Cloud Sampling is a computational method in point cloud processing that reduces the number of points in a 3D point cloud while preserving its geometric structure and salient features for efficient downstream analysis.
157
Publications
9.2K
Citations
457
Authors
181
Institutions
Publications per year
2017–2026
70
Parents
157
PU-Net: Point Cloud Upsampling Network
Lequan Yu, Xianzhi Li, Chi‐Wing Fu et al. · 2018 · 659 citations
Learning to Upsample by Learning to Sample
Wenze Liu, Hao Lü, Hongtao Fu et al. · 2023 · 615 citations
Estimating surface normals in noisy point cloud data
Niloy J. Mitra, Thai An Nguyen · 2003 · 410 citations
Geometrically stable sampling for the ICP algorithm
Natasha Gelfand, Leslie Ikemoto, Szymon Rusinkiewicz et al. · 2004 · 347 citations
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181
Stanford University
Stanford, United States
9 h-index
22 publications
2.9K citations
Tsinghua University
Beijing, China
7 h-index
17 publications
1.2K citations
ETH Zurich
Zurich, Switzerland
7 h-index
15 publications
1.5K citations

University of Hong Kong
Pok Fu Lam, Hong Kong
6 h-index
10 publications
552 citations

Shanghai Jiao Tong University
Shanghai, China
5 h-index
8 publications
358 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
17 publications
2.5K citations

Zhejiang University
Hangzhou, China
5 h-index
16 publications
375 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
6 publications
369 citations
1–8 of 181
TOG · 10 publications · 460 citations
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Repository · 7 publications · 187 citations
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6 publications · 401 citations
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5 publications · 114 citations
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TVCG · 5 publications · 771 citations
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