3D Object Detection on Rope3D Car category heterologous benchmark (test)
16.45APLeAD-M3D X
Evaluation results
| Method | Links | ||
|---|---|---|---|
| LeAD-M3D XGPF=true2025.12 | 16.45 | 31.34 | |
| LeAD-M3D BGPF=true2025.12 | 15.05 | 30.13 | |
| LeAD-M3D MGPF=true2025.12 | 14.31 | 29.62 | |
| LeAD-M3D SGPF=true2025.12 | 13.33 | 28.59 | |
| GroundMixGPF=true2025.12 | 12.86 | 29.37 | |
| MonoDLEGPF=false2025.12 | 12.16 | 28.39 | |
| MonoFlexGPF=false2025.12 | 11.24 | 27.79 | |
| M3D-RPNGPF=false2025.12 | 11.09 | 28.17 | |
| MonoFlexGPF=true2025.12 | 10.86 | 27.39 | |
| MonoConGPF=true2025.12 | 10.71 | 27.55 | |
| LeAD-M3D NGPF=true2025.12 | 9.67 | 25.46 | |
| CoBEVGPF=false2025.12 | 6.59 | 24.01 | |
| M3D-RPNGPF=true2025.12 | 6.05 | 23.84 | |
| Kinematic3DGPF=true2025.12 | 5.82 | 23.06 | |
| BEVHeightGPF=false2025.12 | 5.41 | 23.09 | |
| BEVFormerGPF=true2025.12 | 3.87 | 21.84 | |
| MonoDLEGPF=true2025.12 | 3.77 | 21.42 | |
| BEVDepthGPF=true2025.12 | 0.85 | 19.38 |