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Papers Benchmarks Datasets Tasks

Image-level Anomaly Detection research benchmarks – Page 3 · SOTA2 Research

Image-level Anomaly Detection

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Real-IAD 10% Noise Ratio (test)

Dinomaly + MeDS

92.36I-AUROC

6

May 27, 2026

Real-IAD 0% Noise Ratio (test)

92.39I-AUROC

6

May 27, 2026

VisA Continual multi-category

0.91Candle

6

Feb 26, 2026

97.1AUROC

6

Feb 26, 2026

MVTec AD Texture Average 1.0 (test)

0.998Image AUROC

6

Feb 26, 2026

0.988Candle

6

Feb 26, 2026

VisA 4-shot (test)

0.891AUROC

6

Feb 26, 2026

VisA 2-shot (test)

88.3AUROC

6

Feb 26, 2026

VisA 1-shot (test)

0.869AUROC

6

Feb 26, 2026

MVTec 1-shot (test)

94.6AUROC

6

Feb 26, 2026

93.37AUROC

5

Mar 4, 2026

MVTec 1.0 (test)

86.5AUC

5

Feb 26, 2026

VisA 8-1 x 4 with 4 Steps setting

84.7A-AUROC

5

Feb 26, 2026

VisA 8-4 with 1 Step setting

85.3A-AUROC

5

Feb 26, 2026

VisA 11-1 with 1 Step setting

0.916A-AUROC

5

Feb 26, 2026

MVTec AD zipper

100AUROC

4

Feb 26, 2026

100AUROC

4

Feb 26, 2026

MVTec AD toothbrush

100AUROC

4

Feb 26, 2026

1AUROC

4

Feb 26, 2026

MVTec AD leather

100AUROC

4

Feb 26, 2026

MVTec AD hazelnut

100AUROC

4

Feb 26, 2026

MVTec AD carpet

100AUROC

4

Feb 26, 2026

MVTec AD capsule

100AUROC

4

Feb 26, 2026

MVTec AD bottle

100AUROC

4

Feb 26, 2026

Page 3 of 3

Popular datasets

MVTec AD VisA MVTec BTAD Real-IAD

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