Depth Anomaly Detection And Segmentation On
평가 지표
Detection AUROC
Segmentation AUPRO
Segmentation AUROC
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Detection AUROC | Segmentation AUPRO | Segmentation AUROC |
|---|---|---|---|
| complementary-pseudo-multimodal-feature-for | 0.8918 | 0.9145 | 0.9730 |
| transfusion-a-transparency-based-diffusion | 0.957 | 0.947 | - |
| the-mvtec-3d-ad-dataset-for-unsupervised-3d | 0.546 | 0.374 | - |
| complementary-pseudo-multimodal-feature-for | 0.9515 | 0.9293 | 0.9781 |
| complementary-pseudo-multimodal-feature-for | 0.8304 | 0.9230 | 0.9780 |
| an-empirical-investigation-of-3d-anomaly | 0.675 | 0.755 | 0.930 |
| an-empirical-investigation-of-3d-anomaly | 0.727 | 0.910 | 0.974 |
| an-empirical-investigation-of-3d-anomaly | 0.573 | 0.442 | 0.771 |
| cheating-depth-enhancing-3d-surface-anomaly | 0.922 | 0.907 | - |
| an-empirical-investigation-of-3d-anomaly | 0.696 | 0.5572 | 0.817 |
| the-mvtec-3d-ad-dataset-for-unsupervised-3d | 0.523 | 0.143 | - |
| the-mvtec-3d-ad-dataset-for-unsupervised-3d | 0.546 | 0.203 | - |
| an-empirical-investigation-of-3d-anomaly | 0.559 | 0.771 | 0.930 |