Object Localization On Kitti Pedestrians Hard
评估指标
AP
评测结果
各个模型在此基准测试上的表现结果
模型名称 | AP | Paper Title | Repository |
|---|---|---|---|
| Frustum PointNets | 47.2% | Frustum PointNets for 3D Object Detection from RGB-D Data | - |
| VoxelNet | 38.11% | VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection | - |
| Frustrum-PointPillars | 48.30 % | Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDAR |
0 of 3 row(s) selected.