1-shot classification on tiered-ImageNet (test)
71.71AccuracyRobust 20 Full
Evaluation Results
| Method | Links | |
|---|---|---|
| Robust 20 FullInput size=224, Network=ResNet2019.03 | 71.71 | |
| RFS+distBackbone=ResNet-12, Number of Parameters=8.0M, Input Size=84, MACs=3.5G, Supervision Type=sup.2022.07 | 71.52 | |
| CC+RotBackbone=WRN-28-10, Number of Parameters=36.5M, Input Size=84, MACs=41G, Supervision Type=sup.+ssl2022.07 | 70.53 | |
| Robust 20-distInput size=224, Network=ResNet2019.03 | 70.44 | |
| Robust+distBackbone=ResNet-18, Number of Parameters=11.2M, Input Size=224, MACs=1.8G, Supervision Type=sup.2022.07 | 70.44 | |
| FEATBackbone=WRN-28-10, Number of Parameters=36.5M, Input Size=84, MACs=41G, Supervision Type=sup.2022.07 | 70.41 | |
| UniSiam+distBackbone=ResNet-50, Number of Parameters=23.5M, Input Size=224, MACs=4.1G, Supervision Type=unsup.2022.07 | 69.6 | |
| Centroid AlignmentBackbone=ResNet-18, Number of Parameters=11.2M, Input Size=224, MACs=1.8G, Supervision Type=sup.2022.07 | 69.29 | |
| UniSiamBackbone=ResNet-50, Number of Parameters=23.5M, Input Size=224, MACs=4.1G, Supervision Type=unsup.2022.07 | 69.11 | |
| BMLBackbone=ResNet-12, Number of Parameters=8.0M, Input Size=84, MACs=3.5G, Supervision Type=sup.2022.07 | 68.99 | |
| UniSiam+distBackbone=ResNet-34, Number of Parameters=21.3M, Input Size=224, MACs=3.6G, Supervision Type=unsup.2022.07 | 68.65 | |
| Mean CentroidInput size=224, Network=ResNet2019.03 | 68.33 | |
| UniSiamBackbone=ResNet-34, Number of Parameters=21.3M, Input Size=224, MACs=3.6G, Supervision Type=unsup.2022.07 | 67.57 | |
| UniSiam+distBackbone=ResNet-18, Number of Parameters=11.2M, Input Size=224, MACs=1.8G, Supervision Type=unsup.2022.07 | 67.01 | |
| LEOInput size=80, Network=WideResNet2019.03 | 66.33 | |
| LEOBackbone=WRN-28-10, Number of Parameters=36.5M, Input Size=84, MACs=41G, Supervision Type=sup.2022.07 | 66.33 | |
| MetaOptNetBackbone=ResNet-12, Number of Parameters=8.0M, Input Size=84, MACs=3.5G, Supervision Type=sup.2022.07 | 65.99 | |
| UniSiamBackbone=ResNet-18, Number of Parameters=11.2M, Input Size=224, MACs=1.8G, Supervision Type=unsup.2022.07 | 65.18 | |
| SimSiamBackbone=ResNet-18, Number of Parameters=11.2M, Input Size=224, MACs=1.8G, Supervision Type=unsup., implementation=authors2022.07 | 64.05 | |
| SimCLRBackbone=ResNet-18, Number of Parameters=11.2M, Input Size=224, MACs=1.8G, Supervision Type=unsup., implementation=authors2022.07 | 63.38 | |
| TADAMInput size=84, Network=ResNet2019.03 | 62.13 |