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Models/RD4AD

RD4AD

Reported on 10 benchmarks across 3 tasks · 1 paper · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology8 results

Anomaly DetectiononMVTec LOCO AD
Segmentation AU-sPRO (until FPR 5%)· 2022-01-26
63.7
best: 83.2 (SAM-LAD)
SOTA
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703
Anomaly DetectiononMVTec LOCO AD
Avg. Detection AUROC· 2022-01-26
78.7
best: 95.3 (CSAD)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703
Anomaly DetectiononMVTec LOCO AD
Detection AUROC (only logical)· 2022-01-26
69.4
best: 98.1 (PSAD)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703
Anomaly DetectiononMVTec LOCO AD
Detection AUROC (only structural)· 2022-01-26
88
best: 95.9 (PUAD-M)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703
Anomaly DetectiononGoodsAD
AUPR· 2022-01-26
68.2
best: 86.1 (PatchCore-100%)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703
Anomaly DetectiononGoodsAD
AUROC· 2022-01-26
66.5
best: 86.1 (MiniMaxAD-fr)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703
2D ClassificationonGoodsAD
AUPR· 2022-01-26
68.2
best: 86.1 (PatchCore-100%)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703
2D ClassificationonGoodsAD
AUROC· 2022-01-26
66.5
best: 86.1 (MiniMaxAD-fr)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703

Computer Vision2 results

Anomaly ClassificationonGoodsAD
AUPR· 2022-01-26
68.2
best: 86.1 (PatchCore-100%)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703
Anomaly ClassificationonGoodsAD
AUROC· 2022-01-26
66.5
best: 86.1 (MiniMaxAD-fr)
Anomaly Detection via Reverse Distillation from One-Class Embedding arXiv:2201.10703