Research map / Point clouds / Segmentation and detection
LiDAR-Based Panoptic Segmentation via Dynamic Shifting Network
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use DS-Net instead of the strongest listed baseline | LiDAR panoptic segmentation · SemanticKITTI validation | PQ: 51.7 -> 57.7 | Helped |
| Use DS-Net instead of the strongest listed baseline | LiDAR panoptic segmentation · SemanticKITTI test | PQ: 53.3 -> 55.9 | Helped |
| Use DS-Net instead of the strongest listed baseline | LiDAR panoptic segmentation · nuScenes validation | PQ: 40.1 -> 42.5 | Helped |
| Add consensus-driven fusion to the bare backbone (ablation) | DS-Net backbone · SemanticKITTI validation | PQ | Helped |
| Add dynamic shifting to the backbone with fusion (ablation) | DS-Net backbone with fusion · SemanticKITTI validation | PQTh: +3.2% | Helped |
| Replace dynamic shifting with BFS, DBSCAN, HDBSCAN, or Mean Shift (ablation) | DS-Net · SemanticKITTI validation | PQ | Hurt |
| Directly regress bandwidth instead of weighting bandwidth candidates (ablation) | Dynamic shifting module · SemanticKITTI validation | PQ | Hurt |
| Vary bandwidth candidate settings within the tested range (ablation) | DS-Net · SemanticKITTI validation | PQ: 57.4–57.7 | No clear effect |
| Use 1 rather than 4 dynamic shifting iterations (ablation) | DS-Net · SemanticKITTI validation | PQ: 57.7 -> 57.0 | Hurt |
| Use 5 rather than 4 dynamic shifting iterations (ablation) | DS-Net · SemanticKITTI validation | PQ: 57.7 -> 57.5 | Hurt |
Closest papers by meaning
- Panoptic-PolarNet: Proposal-Free LiDAR Point Cloud Panoptic Segmentation (CVPR 2021 · similarity 0.93)
- Panoptic-PHNet: Towards Real-Time and High-Precision LiDAR Panoptic Segmentation via Clustering Pseudo Heatmap (CVPR 2022 · similarity 0.93)
- How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic Segmentation (ICML 2025 · similarity 0.89)
- PC-BEV: An Efficient Polar-Cartesian BEV Fusion Framework for LiDAR Semantic Segmentation (AAAI 2025 · similarity 0.89)
- Beyond the Label Itself: Latent Labels Enhance Semi-supervised Point Cloud Panoptic Segmentation (AAAI 2024 · similarity 0.88)
- Multi-Space Alignments Towards Universal LiDAR Segmentation (CVPR 2024 · similarity 0.88)
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