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Models/MC4AD

MC4AD

Reported on 16 benchmarks across 2 tasks · 1 paper · 14 SOTA

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

Methodology9 results

Anomaly DetectiononAnomaly-ShapeNet
O-AUROC· uses extra data· 2025-05-09
0.909
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
Anomaly DetectiononAnomaly-ShapeNet
P-AUROC· uses extra data· 2025-05-09
0.91
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
Anomaly DetectiononReal 3D-AD
Mean Performance of P. and O. · uses extra data· 2025-05-09
0.8115
best: 0.821 (DUS-Net)
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
Anomaly DetectiononReal 3D-AD
Object AUROC· uses extra data· 2025-05-09
0.786
best: 0.802 (PASDF)
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
Anomaly DetectiononReal 3D-AD
Point AUROC· uses extra data· 2025-05-09
0.837
best: 0.898 (GLFM)
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
Anomaly DetectiononAnomaly-ShapeNet10
O-AUROC· uses extra data· 2025-05-09
0.888
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
Anomaly DetectiononAnomaly-ShapeNet10
P-AUROC· uses extra data· 2025-05-09
0.937
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
Anomaly DetectiononMVTEC 3D-AD
Detection AUROC· uses extra data· 2025-05-09
0.954
best: 93.7 (AST)
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
Anomaly DetectiononMVTEC 3D-AD
Segmentation AUROC· uses extra data· 2025-05-09
0.946
best: 97.6 (AST)
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901

Computer Vision7 results

3D Anomaly DetectiononAnomaly-ShapeNet
O-AUROC· uses extra data· 2025-05-09
0.909
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
3D Anomaly DetectiononAnomaly-ShapeNet
P-AUROC· uses extra data· 2025-05-09
0.91
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
3D Anomaly DetectiononReal 3D-AD
Mean Performance of P. and O. · uses extra data· 2025-05-09
0.8115
best: 0.821 (DUS-Net)
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
3D Anomaly DetectiononReal 3D-AD
Object AUROC· uses extra data· 2025-05-09
0.786
best: 0.802 (PASDF)
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
3D Anomaly DetectiononReal 3D-AD
Point AUROC· uses extra data· 2025-05-09
0.837
best: 0.898 (GLFM)
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
3D Anomaly DetectiononAnomaly-ShapeNet10
O-AUROC· uses extra data· 2025-05-09
0.888
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901
3D Anomaly DetectiononAnomaly-ShapeNet10
P-AUROC· uses extra data· 2025-05-09
0.937
SOTA
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection arXiv:2505.05901