Image Classification on ImageNet (Top-1 Accuracy and Efficiency)
76.15Top-1 Accuracy (%)ResNet-50
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| ResNet-50Backbone=ResNet-502025.02 | 76.15 | 0 | 0 | 0 | |
| sTLP-IBBackbone=ResNet-502025.02 | 76.12 | 57 | 55 | -0.03 | |
| CSDBackbone=ResNet-502025.02 | 76.11 | 54 | 41 | -0.04 | |
| sGLP-IBBackbone=ResNet-502025.02 | 76.1 | 57 | 55 | -0.05 | |
| NPPMBackbone=ResNet-502025.02 | 75.96 | 56 | — | -0.19 | |
| NORTONBackbone=ResNet-502025.02 | 75.95 | 64 | 59 | -0.2 | |
| LRF-60Backbone=ResNet-502025.02 | 75.71 | 56 | — | -0.44 | |
| CCBackbone=ResNet-502025.02 | 75.59 | 53 | — | -0.56 | |
| DPFPSBackbone=ResNet-502025.02 | 75.55 | 46 | — | -0.6 | |
| APIBBackbone=ResNet-502025.02 | 75.37 | 62 | 58 | -0.78 | |
| SCOPBackbone=ResNet-502025.02 | 75.26 | 55 | — | -0.89 | |
| RandomBackbone=ResNet-502025.02 | 75.13 | 49 | 54 | -1.02 | |
| MFPBackbone=ResNet-502025.02 | 74.86 | 54 | — | -1.29 | |
| DECOREBackbone=ResNet-502025.02 | 72.06 | 61 | — | -4.09 | |
| HrankBackbone=ResNet-502025.02 | 71.98 | 62 | 62 | -4.17 |