Birds Eye View Object Detection On Kitti Cars
Métriques
AP
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | AP | Paper Title | Repository |
---|---|---|---|
PointPillars | 86.1% | PointPillars: Fast Encoders for Object Detection from Point Clouds | |
PIXOR | 77.05% | PIXOR: Real-time 3D Object Detection from Point Clouds | |
STD | 87.76% | STD: Sparse-to-Dense 3D Object Detector for Point Cloud | - |
AVOD-FPN | 83.79% | Joint 3D Proposal Generation and Object Detection from View Aggregation | |
SE-SSD | 91.84% | SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud | |
CIA-SSD | 89.84 % | CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud | |
Patches | 86.55% | Patch Refinement -- Localized 3D Object Detection | - |
PV-RCNN | 90.65% | PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection | |
VoxelNet | 79.26% | VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection |
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