Papers › Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation
Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation
Hui Zhou, Xinge Zhu, Xiao Song, Yuexin Ma, Zhe Wang, Hongsheng Li, Dahua Lin
State-of-the-art methods for large-scale driving-scene LiDAR semantic segmentation often project and process the point clouds in the 2D space. The projection methods includes spherical projection, bird-eye view projection, etc. Although this process makes the point cloud suitable for the 2D CNN-based networks, it inevitably alters and abandons the 3D topology and geometric relations. A straightforward solution to tackle the issue of 3D-to-2D projection is to keep the 3D representation and process the points in the 3D space. In this work, we first perform an in-depth analysis for different representations and backbones in 2D and 3D spaces, and reveal the effectiveness of 3D representations and networks on LiDAR segmentation. Then, we develop a 3D cylinder partition and a 3D cylinder convolution based framework, termed as Cylinder3D, which exploits the 3D topology relations and structures of driving-scene point clouds. Moreover, a dimension-decomposition based context modeling module is introduced to explore the high-rank context information in point clouds in a progressive manner. We evaluate the proposed model on a large-scale driving-scene dataset, i.e. SematicKITTI. Our method achieves state-of-the-art performance and outperforms existing methods by 6% in terms of mIoU.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Object Detection | nuScenes | Reconfig PP v3 | NDS | 0.59 | #192 of 372 | Archive leaderboard | report |
| 3D Object Detection | nuScenes | Reconfig PP v3 | mAAE | 0.24 | #192 of 372 | Archive leaderboard | report |
| 3D Object Detection | nuScenes | Reconfig PP v3 | mAOE | 0.44 | #192 of 372 | Archive leaderboard | report |
| 3D Object Detection | nuScenes | Reconfig PP v3 | mAP | 0.49 | #192 of 372 | Archive leaderboard | report |
| 3D Object Detection | nuScenes | Reconfig PP v3 | mASE | 0.24 | #192 of 372 | Archive leaderboard | report |
| 3D Object Detection | nuScenes | Reconfig PP v3 | mATE | 0.33 | #192 of 372 | Archive leaderboard | report |
| 3D Object Detection | nuScenes | Reconfig PP v3 | mAVE | 0.27 | #192 of 372 | Archive leaderboard | report |
| 3D Semantic Segmentation | WildScenes | Cylinder3D | mIoU | 40.07 | #1 of 4 | Archive leaderboard | report |
| LIDAR Semantic Segmentation | nuScenes | Cylinder3D++ | test mIoU | 0.78 | #14 of 36 | 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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