Image Classification on CIFAR-10 standard (test) (Top-1 Error Rate)
4.08Top-1 Error RateDash (RA)
Evaluation Results
| Method | Links | |
|---|---|---|
| Dash (RA)Number of labels=4000, Backbone=Wide ResNet-28-22021.09 | 4.08 | |
| Dash (CTA)Number of labels=4000, Backbone=Wide ResNet-28-22021.09 | 4.13 | |
| FixMatch (RA)Number of labels=4000, Backbone=Wide ResNet-28-22021.09 | 4.26 | |
| FixMatch (CTA)Number of labels=4000, Backbone=Wide ResNet-28-22021.09 | 4.31 | |
| RYS (FixMatch)Number of labels=4000, Backbone=Wide ResNet-28-22021.09 | 4.35 | |
| Dash (RA)Number of labels=250, Backbone=Wide ResNet-28-22021.09 | 4.56 | |
| ReMixMatchNumber of labels=4000, Backbone=Wide ResNet-28-22021.09 | 4.72 | |
| RYS (UDA)Number of labels=4000, Backbone=Wide ResNet-28-22021.09 | 4.75 | |
| Dash (CTA)Number of labels=250, Backbone=Wide ResNet-28-22021.09 | 4.78 | |
| UDANumber of labels=4000, Backbone=Wide ResNet-28-22021.09 | 4.88 | |
| RYS (FixMatch)Number of labels=250, Backbone=Wide ResNet-28-22021.09 | 5.05 | |
| FixMatch (CTA)Number of labels=250, Backbone=Wide ResNet-28-22021.09 | 5.07 | |
| FixMatch (RA)Number of labels=250, Backbone=Wide ResNet-28-22021.09 | 5.07 | |
| ReMixMatchNumber of labels=250, Backbone=Wide ResNet-28-22021.09 | 5.44 | |
| RYS (UDA)Number of labels=250, Backbone=Wide ResNet-28-22021.09 | 5.53 | |
| MixMatchNumber of labels=4000, Backbone=Wide ResNet-28-22021.09 | 6.42 | |
| UDANumber of labels=250, Backbone=Wide ResNet-28-22021.09 | 8.82 | |
| Dash (CTA)Number of labels=40, Backbone=Wide ResNet-28-22021.09 | 9.16 | |
| Mean TeacherNumber of labels=4000, Backbone=Wide ResNet-28-22021.09 | 9.19 | |
| MixMatchNumber of labels=250, Backbone=Wide ResNet-28-22021.09 | 11.05 | |
| FixMatch (CTA)Number of labels=40, Backbone=Wide ResNet-28-22021.09 | 11.39 | |
| Dash (RA)Number of labels=40, Backbone=Wide ResNet-28-22021.09 | 13.22 | |
| FixMatch (RA)Number of labels=40, Backbone=Wide ResNet-28-22021.09 | 13.81 | |
| Π-ModelNumber of labels=4000, Backbone=Wide ResNet-28-22021.09 | 14.01 | |
| Pseudo-LabelingNumber of labels=4000, Backbone=Wide ResNet-28-22021.09 | 16.09 | |
| ReMixMatchNumber of labels=40, Backbone=Wide ResNet-28-22021.09 | 19.1 | |
| UDANumber of labels=40, Backbone=Wide ResNet-28-22021.09 | 29.05 | |
| Mean TeacherNumber of labels=250, Backbone=Wide ResNet-28-22021.09 | 32.32 | |
| MixMatchNumber of labels=40, Backbone=Wide ResNet-28-22021.09 | 47.54 | |
| Pseudo-LabelingNumber of labels=250, Backbone=Wide ResNet-28-22021.09 | 49.78 | |
| Π-ModelNumber of labels=250, Backbone=Wide ResNet-28-22021.09 | 54.26 |