GrowSP: Unsupervised Semantic Segmentation of 3D Point Clouds
Zihui Zhang, Bo Yang, Bing Wang, Bo Li
2023Year
14Top-tier citations
Abstract
Input Point Cloud Initial Superpoints Progressively Growing Superpoints Prediction by GrowSP Ground Truth Figure 1. Given an input point cloud with complex structures from S3DIS dataset [2], our GrowSP automatically discovers accurate semantic classes simply by progressively growing superpoints, without needing any human labels in training.
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Install the CLIlune papers fulltext 7b1a237a-64bd-43e6-8366-7ecdd0d7ae4bCited by top-tier papers14
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- HUNTER: Unsupervised Human-Centric 3D Detection via Transferring Knowledge from Synthetic Instances to Real ScenesYichen Yao, Zimo Jiang, Yujing Sun, Zhencai Zhu et al.CVPR 2024 · 4 citations
- PointGS: Semantic-Consistent Unsupervised 3D Point Cloud Segmentation with 3D Gaussian SplattingYixiao Song, Qingyong Li, Wen Wang, Zhicheng YanCVPR 2026 · 4 citations
Builds on25
- SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR SequencesJens Behley, Martin Garbade, Andres Milioto, Jan Quenzel et al.ICCV 2019 · 2,345 citations
- Invariant Information Clustering for Unsupervised Image Classification and SegmentationXu Ji, Andrea Vedaldi, João F. HenriquesICCV 2019 · 956 citations
- Self-Supervised Pretraining of 3D Features on any Point-CloudZaiwei Zhang, Rohit Girdhar, Armand Joulin, Ishan MisraICCV 2021 · 333 citations
- Unsupervised Point Cloud Pre-training via Occlusion CompletionHanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby et al.ICCV 2021 · 323 citations
- Unsupervised Semantic Segmentation by Contrasting Object Mask ProposalsWouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Luc Van GoolICCV 2021 · 285 citations
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- Superpoint Network for Point Cloud OversegmentationLe Hui, Jia Yuan, Mingmei Cheng, Jin Xie et al.ICCV 2021 · 50 citations
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