Table 4.
Test error (%) on the smallNORB classification task.
| Method | Reconstruction | Parameters (K) | smallNORB (%) |
|---|---|---|---|
| Our baseline | No | 198 | 5.9 |
| Base-CapsNet | No | 167 | 4.58 |
| Our baseline | Yes | 198 | 4.59 |
| Base-CapsNet | Yes | 167 | 4.33 |
| Efficient-CapsNet | Yes | 151 | |
| Baseline14 | No | 4200 | 5.2 |
| Matrix-CapsNet with EM routing14 | No | 310 | 1.8 ()* |
| CapsNet10 | Yes | 6800 | 3.77 |
| VB-Routig16 | Yes | 310 |
All methodologies are reported with their number of parameters andthe presence of the reconstruction regularizer during the training phase. * indicates the results from our experiments.