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3D Instance Segmentation On Stpls3D
Metrics
AP
AP25
AP50
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||||
|---|---|---|---|---|---|
| EASE | 64.5 | 86.9 | 80.8 | Edge-Aware 3D Instance Segmentation Network with Intelligent Semantic Prior | - |
| Mask3D | 57.3 | 81.6 | 74.3 | Mask3D: Mask Transformer for 3D Semantic Instance Segmentation | |
| TD3D | 54.3 | - | 69.8 | Top-Down Beats Bottom-Up in 3D Instance Segmentation | - |
| Spherical Mask | 52.2 | - | 68.3 | Spherical Mask: Coarse-to-Fine 3D Point Cloud Instance Segmentation with Spherical Representation | |
| ISBNet | 49.2 | - | 64.0 | ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolution | |
| SoftGroup | 47.3 | 71.4 | 63.1 | SoftGroup for 3D Instance Segmentation on Point Clouds | |
| SoftGroup++ | 46.5 | 71.8 | 62.9 | Scalable SoftGroup for 3D Instance Segmentation on Point Clouds | |
| HAIS | 35.1 | 52.8 | 46.7 | Hierarchical Aggregation for 3D Instance Segmentation | |
| PointGroup | 23.3 | 48.6 | 38.5 | PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation |
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