Out-of-Distribution Detection on CIFAR-100 (ID) vs Places365 (Far-OOD) (OpenOOD v1.5 Test)
44.07FPR@95GradNorm
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| GradNormBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 44.07 | 88.41 | |
| ViMBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 46.51 | 86.53 | |
| SHEBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 46.96 | 87.4 | |
| ReActBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 47.42 | 87.14 | |
| RMDSBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 49.79 | 84.64 | |
| KNNBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 50.66 | 85.39 | |
| EPDBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 52.44 | 85.21 | |
| MDSBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 56.47 | 82.55 | |
| EBOBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 64.07 | 83.81 | |
| MLSBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 64.07 | 83.58 | |
| TempScaleBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 64.19 | 82.13 | |
| GENBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 64.43 | 83.8 | |
| MSPBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 64.56 | 80.8 | |
| DICEBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 65.11 | 82.65 | |
| OpenMaxBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 66.2 | 81.15 | |
| ASHBackbone=ViT-B/16, Pre-trained Model=google/vit-base-patch16-224-in21k, ID Accuracy=84.78%, Evaluation Protocol=fine-tuned2026.04 | 91.72 | 52.57 |