Photo To Rest Generalization On Pacs
Metrics
Accuracy
Results
Performance results of various models on this benchmark
| Paper Title | ||
|---|---|---|
| Crafting-Shifts(ResNet18) | 65.85 | Crafting Distribution Shifts for Validation and Training in Single Source Domain Generalization |
| ProRandConv (ResNet18) | 62.89 | Progressive Random Convolutions for Single Domain Generalization |
| Crafting-Shifts(AlexNet) | 60.97 | Crafting Distribution Shifts for Validation and Training in Single Source Domain Generalization |
| MCL (ResNet18) | 59.6 | Meta-causal Learning for Single Domain Generalization |
| ABA (ResNet18) | 59.04 | Adversarial Bayesian Augmentation for Single-Source Domain Generalization |
| MetaCNN (AlexNet) | 57.17 | Meta Convolutional Neural Networks for Single Domain Generalization |
| CADA (ResNet18) | 56.65 | Center-aware Adversarial Augmentation for Single Domain Generalization |
| PACS (AlexNet) | 55.24 | Learning to Diversify for Single Domain Generalization |
0 of 8 row(s) selected.