Research map / Detection and segmentation / 3D detection and driving
nuScenes: A Multimodal Dataset for Autonomous Driving
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Accumulate multiple lidar sweeps instead of using a single sweep (ablation) | PointPillars · nuScenes val | NDS: 31.8 -> 44.8 | Helped |
| Accumulate multiple lidar sweeps instead of using a single sweep (ablation) | PointPillars · nuScenes val | mAVE: 1.21 -> 0.30 | Helped |
| Replace KITTI pretraining with ImageNet pretraining (ablation) | PointPillars with 10 sweeps · nuScenes val | NDS: 44.8 -> 44.9 | No clear effect |
| Filter predictions and ground truth to boxes on the semantic map prior | PointPillars · nuScenes val bicycle | AP: 1% -> 30% | Helped |
| Use more training data (ablation) | PointPillars compared with SSD+3D · nuScenes val | mAP | Helped |
Closest papers by meaning
- Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving (CVPR 2025 · similarity 0.86)
- The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset (NeurIPS 2026 · similarity 0.86)
- MAN TruckScenes: A multimodal dataset for autonomous trucking in diverse conditions (NeurIPS 2024 · similarity 0.86)
- SDAC: A Multimodal Synthetic Dataset for Anomaly and Corner Case Detection in Autonomous Driving (AAAI 2024 · similarity 0.85)
- OpenAD: Open-World Autonomous Driving Benchmark for 3D Object Detection (NeurIPS 2025 · similarity 0.84)
- DriveGEN: Generalized and Robust 3D Detection in Driving via Controllable Text-to-Image Diffusion Generation (CVPR 2025 · similarity 0.84)
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