3D classification on ScanObjectNN Scan-O (test)
85.3AccuracyKPConv
Evaluation Results
| Method | Links | |
|---|---|---|
| KPConvArchitecture=ANN, Input=Point, Param (M)=14.3, T x D=N/A2025.05 | 85.3 | |
| Spike-driven PointFormerArchitecture=SNN, Input=Point, Param (M)=7.69, Energy (mJ)=5.1, T x D=1 × 42025.05 | 82.1 | |
| Spike-driven PointFormerArchitecture=SNN, Input=Point, Param (M)=22.1, Energy (mJ)=9.4, T x D=1 × 42025.05 | 81.7 | |
| PointformerArchitecture=ANN, Input=Point, Param (M)=4.91, Energy (mJ)=30.1, T x D=N/A2025.05 | 81.3 | |
| P2SResLNetArchitecture=SNN, Input=Point, Param (M)=14.3, T x D=4 × 12025.05 | 81.2 | |
| E-3DSNN-LArchitecture=SNN, Input=Voxel, Param (M)=17.7, Energy (mJ)=0.26, T x D=1 × 42025.05 | 80.2 | |
| Spike Point TransFormerArchitecture=ANN, Input=Point, Param (M)=9.6, Energy (mJ)=21.1, T x D=4 × 12025.05 | 80.1 | |
| E-3DANN-SArchitecture=ANN, Input=Voxel, Param (M)=3.27, Energy (mJ)=0.13, T x D=1 × 42025.05 | 79.7 | |
| E-3DSNN-SArchitecture=SNN, Input=Voxel, Param (M)=3.27, Energy (mJ)=0.02, T x D=1 × 42025.05 | 78.7 | |
| Spike PointNetArchitecture=SNN, Input=Point, Param (M)=3.47, Energy (mJ)=0.24, T x D=1 × 42025.05 | 70 | |
| PointNetArchitecture=ANN, Input=Point, Param (M)=3.27, Energy (mJ)=2.02, T x D=N/A2025.05 | 68.2 | |
| SpikingPointNetArchitecture=SNN, Input=Point, Param (M)=3.47, Energy (mJ)=0.91, T x D=16 × 12025.05 | 66.6 |