Object Localization On Kitti Pedestrians
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AP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| Frustrum-PointPillars | 52.23 % | Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDAR |
| Frustum PointNets | 50.22% | Frustum PointNets for 3D Object Detection from RGB-D Data |
| VoxelNet | 40.74% | VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection |
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