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Codesota · Tasks · Anomaly DetectionHome/Tasks/Industrial Inspection/Anomaly Detection

Anomaly Detection.

Detecting defects and anomalies in manufacturing (MVTec AD, VisA).

7
Datasets
27
Results
auroc
Canonical metric
§ 02 · Canonical benchmark

The reference dataset.

MVTec AD

5,354 high-resolution images across 15 object and texture categories. The gold standard for industrial anomaly detection with pixel-level annotations.

Primary metric: auroc
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§ 03 · Top 10

Leading models.

Leading models on MVTec AD.

#ModelaurocYearSource
SimpleNet99.62025paper ↗
2FastFlow99.42025paper ↗
3PatchCore99.12025paper ↗
4EfficientAD99.12025paper ↗
5Reverse Distillation98.52025paper ↗
6CFLOW-AD98.32025paper ↗
7DRAEM98.02025paper ↗
8PaDiM97.92025paper ↗
9AnomalyGPT97.4paper ↗

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§ 04 · All datasets

Tracked datasets.

7 datasets tracked for this task.

MVTec AD
CANONICAL
9 results · auroc
Top: SimpleNet 99.6
KolektorSDD2
6 results · auroc
Top: SuperSimpleNet 97.4
MVTec 3D-AD
6 results · auroc
Top: CMDR-IAD 97.3
VisA
3 results · auroc
Top: SimpleNet 95.5
NEU-DET
1 result · map
Top: DefectDet (ResNet) 78.4
Severstal Steel Defect
1 result · dice
Top: YOLOv8 (Weld Detection) 91.2
Weld Defect X-Ray
1 result · map
Top: YOLOv8 (Weld Detection) 87.3
§ 05 · Related tasks

Other tasks in Industrial Inspection.

Steel Defect DetectionSurface Defect DetectionWeld Inspection
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