Papers › PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, Jiaya Jia
Instance segmentation is an important task for scene understanding. Compared to the fully-developed 2D, 3D instance segmentation for point clouds have much room to improve. In this paper, we present PointGroup, a new end-to-end bottom-up architecture, specifically focused on better grouping the points by exploring the void space between objects. We design a two-branch network to extract point features and predict semantic labels and offsets, for shifting each point towards its respective instance centroid. A clustering component is followed to utilize both the original and offset-shifted point coordinate sets, taking advantage of their complementary strength. Further, we formulate the ScoreNet to evaluate the candidate instances, followed by the Non-Maximum Suppression (NMS) to remove duplicates. We conduct extensive experiments on two challenging datasets, ScanNet v2 and S3DIS, on which our method achieves the highest performance, 63.6% and 64.0%, compared to 54.9% and 54.4% achieved by former best solutions in terms of mAP with IoU threshold 0.5.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Instance Segmentation | S3DIS | PointGroup | AP@50 | 64.0 | #11 of 21 | Archive leaderboard | report |
| 3D Instance Segmentation | S3DIS | PointGroup | mPrec | 69.6 | #11 of 21 | Archive leaderboard | report |
| 3D Instance Segmentation | S3DIS | PointGroup | mRec | 69.2 | #11 of 21 | Archive leaderboard | report |
| 3D Instance Segmentation | STPLS3D | PointGroup | AP | 23.3 | #9 of 9 | Archive leaderboard | report |
| 3D Instance Segmentation | STPLS3D | PointGroup | AP25 | 48.6 | #9 of 9 | Archive leaderboard | report |
| 3D Instance Segmentation | STPLS3D | PointGroup | AP50 | 38.5 | #9 of 9 | Archive leaderboard | report |
| 3D Instance Segmentation | ScanNet(v2) | PointGroup | mAP | 40.7 | #20 of 32 | Archive leaderboard | report |
| 3D Instance Segmentation | ScanNet(v2) | PointGroup | mAP @ 50 | 63.6 | #20 of 32 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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