Single Source Domain Generalization On Pacs
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Accuracy |
|---|---|
| adversarial-bayesian-augmentation-for-single | 66.36 |
| progressive-random-convolutions-for-single | 68.88 |
| selfreg-self-supervised-contrastive | 59.59 |
| geometric-and-textural-augmentation-for | 65.0 |
| cross-domain-ensemble-distillation-for-domain-2 | 66.5 |
| meta-causal-learning-for-single-domain | 69.86 |
| improved-test-time-adaptation-for-domain | 68.4 |
| crafting-distribution-shifts-for-validation | 70.37 |
| center-aware-adversarial-augmentation-for | 68.41 |
| reducing-domain-gap-via-style-agnostic | 61.9 |