Image Classification on AG-Fashion-MNIST (test) (Transformation Robustness)
44.48Top-1 Accuracy (I=4 Hor)ICPNet
Evaluation results
| Method | Links | ||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ICPNet2025.08 | 44.48 | 42.69 | 42.25 | 47.81 | 68.53 | 77.15 | 77.36 | 73.83 | 48.04 | 46.39 | 42.9 | 50.42 | 52.95 | 68.51 | 69.65 | 38.75 | 34.75 | 23.95 | 18.93 | 13.95 | 36.5 | 59.34 | 61.03 | 34.05 | |
| ConvNeXt-B2025.08 | 19.3 | 10.08 | 10.21 | 21.25 | 10.14 | 9.53 | 10.16 | 11.27 | 12.88 | 9.37 | 9.93 | 16.67 | 14.38 | 12.11 | 10.18 | 10.92 | 10.92 | 20.52 | 10.88 | 12.64 | 10.03 | 12.91 | 10.89 | 7.03 | |
| MambaOut-B2025.08 | 15.97 | 11.2 | 12.58 | 15.28 | 15.93 | 10.04 | 16.07 | 16.44 | 11.4 | 11.05 | 11.09 | 19.64 | 13.44 | 15.53 | 19.12 | 13.97 | 20.82 | 17.07 | 17.29 | 23.33 | 11.59 | 15.06 | 19.84 | 6.49 | |
| Swin-B2025.08 | 12.65 | 9.43 | 8.22 | 4.34 | 5.18 | 12.9 | 12.63 | 10.14 | 11.14 | 12.97 | 17.15 | 3.6 | 2.21 | 10.14 | 12.97 | 17.66 | 6.71 | 12.54 | 6.22 | 9.99 | 6.73 | 10.08 | 10.14 | 10.15 | |
| ResNet1012025.08 | 11.04 | 10.14 | 10.14 | 16.23 | 13.92 | 10.04 | 17.92 | 13.31 | 10.67 | 11.29 | 11.01 | 8.65 | 14.39 | 10.74 | 6.45 | 10.86 | 27.32 | 6.71 | 6.71 | 9.7 | 10.14 | 6.71 | 6.71 | 15.49 | |
| ResNet182025.08 | 10.34 | 10.45 | 10.46 | 16.21 | 15.66 | 17.74 | 11.53 | 24.2 | 10.69 | 12.49 | 12.63 | 18.29 | 9.85 | 10.66 | 10.86 | 9.28 | 54.74 | 6.71 | 6.75 | 38.25 | 10.14 | 6.77 | 6.77 | 7.28 | |
| ViT-L-162025.08 | 10.24 | 8.58 | 10.04 | 8 | 10.23 | 9.66 | 10.14 | 11.46 | 10.08 | 9.8 | 11.77 | 3.53 | 7.69 | 6.71 | 10.89 | 10.53 | 12.98 | 12.33 | 10.13 | 10.74 | 10.14 | 10.14 | 10.06 | 10.53 | |
| VGG162025.08 | 10.13 | 10.14 | 10.14 | 10.22 | 15.85 | 10.14 | 10.14 | 14.75 | 21.02 | 10.14 | 13.29 | 20.64 | 26.07 | 10.04 | 15.59 | 22.8 | 28.93 | 11.25 | 18.29 | 24.55 | 27.94 | 14.86 | 17.29 | 18.3 |