Birds Eye View Object Detection On Kitti Cars 4
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AP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | AP | Paper Title | Repository |
|---|---|---|---|
| PointPillars | 88.35% | PointPillars: Fast Encoders for Object Detection from Point Clouds | |
| STD | 89.66 | STD: Sparse-to-Dense 3D Object Detector for Point Cloud | - |
| CIA-SSD | 93.74 % | CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud | |
| AVOD-FPN | 88.53 | Joint 3D Proposal Generation and Object Detection from View Aggregation | |
| SE-SSD | 95.68% | SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud | |
| PIXOR | 81.7% | PIXOR: Real-time 3D Object Detection from Point Clouds | |
| VoxelNet | 89.35% | VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection | |
| Patches | 89.78 | Patch Refinement -- Localized 3D Object Detection | - |
| PV-RCNN | 94.98 | PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection |
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