3D Instance Segmentation
3D Instance Segmentation is a computer vision task that distinguishes individual object instances in three-dimensional space by assigning unique labels to each entity while preserving their volumetric spatial extent.
155
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10.4K
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698
Authors
241
Institutions
Publications per year
2017–2026
152
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SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
Weiyue Wang, Ronald Yu, Qiangui Huang et al. · 2018 · 592 citations
Objaverse: A Universe of Annotated 3D Objects
Matt Deitke, Dustin Schwenk, Jordi Salvador et al. · 2023 · 587 citations
3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans
Ji Hou, Angela Dai, Matthias NieBner · 2019 · 512 citations
PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
Li Jiang, Hengshuang Zhao, Shaoshuai Shi et al. · 2020 · 461 citations
GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud
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Zhejiang University
Hangzhou, China
7 h-index
33 publications
1.6K citations
Tsinghua University
Beijing, China
7 h-index
22 publications
2.2K citations
RWTH Aachen University
Aachen, Germany
6 h-index
13 publications
852 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
6 h-index
20 publications
3.4K citations
University of Oxford
Oxford, United Kingdom
5 h-index
13 publications
1.1K citations
ETH Zurich
Zurich, Switzerland
5 h-index
14 publications
602 citations

Shanghai Jiao Tong University
Shanghai, China
5 h-index
14 publications
658 citations
SMART Reading
Portland, United States
4 h-index
5 publications
1K citations
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Repository · 22 publications · 1K citations
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5 publications · 123 citations
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5 publications · 144 citations
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Conference · 4 publications · 340 citations
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Conference · 4 publications · 363 citations
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