Point Cloud Scene Understanding is a computational framework that enables the interpretation and semantic abstraction of three-dimensional environments by identifying, categorizing, and contextualizing objects and their spatial relationships within an unstructured point cloud.
235
Publications
18.5K
Citations
877
Authors
282
Institutions
Publications per year
2017–2026
190
Parents
Publications
235
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
Shaoshuai Shi, Chaoxu Guo, Li Jiang et al. · 2020 · 2.1K citations
TopNet: Structural Point Cloud Decoder
Lyne P. Tchapmi, Vineet Kosaraju, Hamid Rezatofighi et al. · 2019 · 521 citations
1–5 of 235
Authors
877
- LD
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- SY
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- ZZ
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- JL
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- BH
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1–5 of 877
Institutions
282
Chinese University of Hong Kong
Hong Kong, Hong Kong
12 h-index
29 publications
8.5K citations
Wuhan University
Wuhan, China
9 h-index
18 publications
532 citations
Tsinghua University
Beijing, China
8 h-index
21 publications
936 citations
Technical University of Munich
Munich, Germany
7 h-index
19 publications
1.7K citations
Carnegie Mellon University
Pittsburgh, United States
7 h-index
20 publications
4K citations
University of Waterloo
Waterloo, Canada
6 h-index
12 publications
2K citations
Nanyang Technological University
Singapore, Singapore
6 h-index
15 publications
815 citations
Hong Kong University of Science and Technology
Hong Kong, Hong Kong
6 h-index
7 publications
768 citations
1–8 of 282
Venues
- arXiv (Cornell University)
Repository · 27 publications · 1.5K citations
18
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- Automation in Construction
11 publications · 1.5K citations
11
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- ISPRS Journal of Photogrammetry and Remote Sensing
8 publications · 987 citations
8
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- Neurocomputing
5 publications · 92 citations
5
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- 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Conference · 5 publications · 487 citations
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1–5