Classification on Camelyon VTAB 1k (test)
88.1AccuracyLoRA_mul+VPT_add + PACE
Evaluation Results
| Method | Links | |
|---|---|---|
| LoRA_mul+VPT_add + PACEPre-training Method=DINO, Backbone=ViT-B/16, Pre-trained on=ImageNet-1K2024.09 | 88.1 | |
| LoRA_mul+VPT_add + PACEPre-training Method=MAE, Backbone=ViT-B/16, Pre-trained on=ImageNet-1K2024.09 | 85.8 | |
| LoRA_mul+VPT_addPre-training Method=DINO, Backbone=ViT-B/16, Pre-trained on=ImageNet-1K2024.09 | 85.4 | |
| LoRA_mul+VPT_addPre-training Method=MAE, Backbone=ViT-B/16, Pre-trained on=ImageNet-1K2024.09 | 82.7 | |
| LinearPre-training Method=DINO, Backbone=ViT-B/16, Pre-trained on=ImageNet-1K2024.09 | 82.5 | |
| LinearPre-training Method=MAE, Backbone=ViT-B/16, Pre-trained on=ImageNet-1K2024.09 | 79.9 | |
| FullPre-training Method=MAE, Backbone=ViT-B/16, Pre-trained on=ImageNet-1K2024.09 | 74.6 | |
| FullPre-training Method=DINO, Backbone=ViT-B/16, Pre-trained on=ImageNet-1K2024.09 | 73.1 |