Anomaly Detection On Aebad S
Metrics
Detection AUROC
Segmentation AUPRO
Results
Performance results of various models on this benchmark
Model Name | Detection AUROC | Segmentation AUPRO | Paper Title | Repository |
|---|---|---|---|---|
| RIAD | 40.0 | 58.2 | Reconstruction by Inpainting for Visual Anomaly Detection | |
| MMR | 84.7 | 89.1 | Industrial Anomaly Detection with Domain Shift: A Real-world Dataset and Masked Multi-scale Reconstruction | |
| DRAEM | 62.5 | 63.6 | DRAEM - A Discriminatively Trained Reconstruction Embedding for Surface Anomaly Detection | |
| ReverseDistillation | 81.0 | 85.6 | Anomaly Detection via Reverse Distillation from One-Class Embedding | |
| PatchCore | 71.0 | 87.8 | Towards Total Recall in Industrial Anomaly Detection | |
| InTra | 44.2 | 74.7 | Inpainting Transformer for Anomaly Detection | |
| NSA | 56.7 | 45.9 | Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization | |
| MSFR | 87.1 | 90.4 | Multi-scale feature reconstruction network for industrial anomaly detection |
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