| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| KITTI (test) | SE-SSD | AP (Easy)95.68 | 47 | 2d ago | |
| KITTI official (test) | NeurOCS-M | AP40 Easy37.5 | 22 | 3d ago | |
| TJ4DRadSet (test) | Ours | BEV mAP49.33 | 21 | 3d ago | |
| KITTI (test) | CaDDN | AP Car (IoU=0.7) Easy27.94 | 16 | 2d ago | |
| KITTI (val) | ContFusion | AP_BEV Easy95.44 | 14 | 3d ago | |
| KITTI official (val) | PCT | Easy AP4047.16 | 13 | 3d ago | |
| Waymo Open Dataset Vehicles (val) | Pillar-based | AP L186.1 | 12 | 3d ago | |
| DAIR-V2X (val) | ImVoxelNet | APBEV R40 (IoU=0.5, easy)51.9 | 9 | 3d ago | |
| Waymo Open Dataset (WOD) (val) | PillarNeXt-B | Vehicle L1 AP94.41 | 5 | 3d ago | |
| KITTI (val) | PIXOR | AP@0.7 (0-30m)87.68 | 3 | 2d ago | |
| KRadar (test) | EchoFusion | AP (BEV) @ IoU=0.369.95 | 3 | 3d ago | |
| Waymo Open Dataset (WOD) 5 sequences, Vehicle, L1 (val) | DetZero | BEV AP (IoU=0.7)95.15 | 3 | 3d ago | |
| KITTI Leaderboard official (test) | DSGN | Pedestrian AP (Easy)26.61 | 3 | 3d ago | |
| RADIal refined 3D ground-truth (test) | EchoFusion | BEV AP@0.7 (Overall)84.92 | 2 | 3d ago |
