Single-Source Domain Generalization
In this task a model is trained in a single source domain and then it is tested in a number of target domains
Papers
Showing 1–10 of 48 papers
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Crafting-Shifts(ResNet18) | Accuracy | 70.37 | — | Unverified |
| 2 | MCL (ResNet18) | Accuracy | 69.86 | — | Unverified |
| 3 | ProRandConv (ResNet18) | Accuracy | 68.88 | — | Unverified |
| 4 | CADA (ResNet18) | Accuracy | 68.41 | — | Unverified |
| 5 | ITTA (ResNet18) | Accuracy | 68.4 | — | Unverified |
| 6 | XDED (ResNet18) | Accuracy | 66.5 | — | Unverified |
| 7 | ABA (ResNet18) | Accuracy | 66.36 | — | Unverified |
| 8 | GeoTexAug (ResNet18) | Accuracy | 65 | — | Unverified |
| 9 | SagNet (ResNet18) | Accuracy | 61.9 | — | Unverified |
| 10 | SelfReg (ResNet18) | Accuracy | 59.59 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Crafting-Shifts(LeNet) | Accuracy | 82.61 | — | Unverified |
| 2 | ProRandConv (LeNet) | Accuracy | 81.35 | — | Unverified |
| 3 | CADA (LeNet) | Accuracy | 80.56 | — | Unverified |
| 4 | MCL (LeNet) | Accuracy | 78.82 | — | Unverified |
| 5 | MetaCNN (LeNet) | Accuracy | 78.76 | — | Unverified |
| 6 | ABA (LeNet) | Accuracy | 76.72 | — | Unverified |
| 7 | L2D (LeNet) | Accuracy | 74.46 | — | Unverified |