Point Cloud Completion
Point Cloud Completion is a computational task in depth estimation that belongs to the broader category of 3D scene reconstruction, specifically defined as the process of generating geometrically accurate and structurally coherent full 3D point clouds from incomplete or sparse depth observations.
176
Publications
13.1K
Citations
642
Authors
202
Institutions
Publications per year
2017–2026
160
176
Wentao Yuan, Tejas Khot, David Held et al. · 2018 · 958 citations
Diffusion Probabilistic Models for 3D Point Cloud Generation
Shitong Luo, Wei Hu · 2021 · 566 citations
TopNet: Structural Point Cloud Decoder
Lyne P. Tchapmi, Vineet Kosaraju, Hamid Rezatofighi et al. · 2019 · 521 citations
PF-Net: Point Fractal Network for 3D Point Cloud Completion
Zitian Huang, Yikuan Yu, Jiawen Xu et al. · 2020 · 493 citations
1–5 of 176
642
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202
Tsinghua University
Beijing, China
13 h-index
45 publications
8.4K citations

Shanghai Jiao Tong University
Shanghai, China
9 h-index
36 publications
3.1K citations

Peking University
Beijing, China
6 h-index
10 publications
1.3K citations

Zhejiang University
Hangzhou, China
6 h-index
23 publications
1.4K citations
National University of Singapore
Singapore, Singapore
6 h-index
15 publications
1.4K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
6 h-index
12 publications
1.1K citations
Kuaishou (China)
Beijing, China
6 h-index
17 publications
2.5K citations
Wuhan University
Wuhan, China
6 h-index
17 publications
1.4K citations
1–8 of 202
Repository · 24 publications · 592 citations
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TPAMI · 9 publications · 547 citations
9
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9 publications · 357 citations
9
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Conference · 6 publications · 1.6K citations
6
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Conference · 6 publications · 490 citations
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