Research map / Detection and segmentation / 3D detection and driving
Semantic Consistency Networks for 3D Object Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add semantic segmentation as an auxiliary jointly trained structure (ablation) | VoteNet BaseNet · SUN RGB-D | mAP@0.25: 57.7 -> 58.7 | Helped |
| Add semantic segmentation as an auxiliary jointly trained structure (ablation) | VoteNet BaseNet · ScanNet | mAP@0.25: 58.6 -> 60.7 | Helped |
| Add semantic voting to combine geometric and semantic cues (ablation) | BaseNet + semantic segmentation · SUN RGB-D | mAP@0.25: 58.7 -> 59.3 | Helped |
| Add semantic voting to combine geometric and semantic cues (ablation) | BaseNet + semantic segmentation · ScanNet | mAP@0.25: 60.7 -> 61.4 | Helped |
| Add semantic consistency loss between box proposals and corresponding semantic points (ablation) | BaseNet + semantic segmentation + semantic voting · SUN RGB-D | mAP@0.25: 59.3 -> 59.9 | Helped |
| Add semantic consistency loss between box proposals and corresponding semantic points (ablation) | BaseNet + semantic segmentation + semantic voting · ScanNet | mAP@0.25: 61.4 -> 63.3 | Helped |
Closest papers by meaning
- Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation (CVPR 2023 · similarity 0.89)
- Weakly Supervised 3D Segmentation via Receptive-Driven Pseudo Label Consistency and Structural Consistency (AAAI 2023 · similarity 0.88)
- Seg2Box: 3D Object Detection by Point-Wise Semantics Supervision (AAAI 2025 · similarity 0.88)
- Associatively Segmenting Instances and Semantics in Point Clouds (CVPR 2019 · similarity 0.87)
- P-SLCR: Unsupervised Point Cloud Semantic Segmentation via Prototypes Structure Learning and Consistent Reasoning (AAAI 2026 · similarity 0.87)
- BFANet: Revisiting 3D Semantic Segmentation with Boundary Feature Analysis (CVPR 2025 · similarity 0.86)
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