Table 1:
Evaluation performance on simulated Dataset A with SNR = 0.06. To clarify, classification, segmentation and structure recovery subnet are individually or dually extracted from DSM-Net, abbreviated as Cls, Seg and Rec Subnet below. ‘-’ indicates incompatible tasks while ‘*’ indicates the model fails to converge.
| Method | Backbone | Segmentation | Classification | |
|---|---|---|---|---|
| Pix acc | mIoU | Obj acc | ||
| DSRF3D-v2[6] | 3D VGG-8 | - | - | * |
| Cls Subnet | 3D ResNet-9 | - | - | 76.24 |
| SSN3D-ED [12] | 3D VGG-8 | 98.99 | 84.68 | - |
| Seg Subnet | 3D ResNet-9 | 99.03 | 87.07 | - |
| Cls+Rec Subnet | 3D ResNet-9 | - | - | 81.87 |
| Cls+Seg Subnet | 3D ResNet-9 | 99.22 | 88.70 | 84.37 |
| DSM-Net | 3D ResNet-9 | 99.21 | 89.00 | 93.75 |