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Models/PO3AD

PO3AD

Reported on 8 benchmarks across 2 tasks · 1 paper · 8 SOTA

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

Methodology4 results

Anomaly DetectiononAnomaly-ShapeNet
O-AUROC· 2024-12-17
0.839
best: 0.909 (MC4AD)
SOTA
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection arXiv:2412.12617
Anomaly DetectiononAnomaly-ShapeNet
P-AUROC· 2024-12-17
0.898
best: 0.91 (MC4AD)
SOTA
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection arXiv:2412.12617
Anomaly DetectiononReal 3D-AD
Mean Performance of P. and O. · 2024-12-17
0.765
best: 0.821 (DUS-Net)
SOTA
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection arXiv:2412.12617
Anomaly DetectiononReal 3D-AD
Object AUROC· 2024-12-17
0.765
best: 0.802 (PASDF)
SOTA
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection arXiv:2412.12617

Computer Vision4 results

3D Anomaly DetectiononAnomaly-ShapeNet
O-AUROC· 2024-12-17
0.839
best: 0.909 (MC4AD)
SOTA
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection arXiv:2412.12617
3D Anomaly DetectiononAnomaly-ShapeNet
P-AUROC· 2024-12-17
0.898
best: 0.91 (MC4AD)
SOTA
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection arXiv:2412.12617
3D Anomaly DetectiononReal 3D-AD
Mean Performance of P. and O. · 2024-12-17
0.765
best: 0.821 (DUS-Net)
SOTA
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection arXiv:2412.12617
3D Anomaly DetectiononReal 3D-AD
Object AUROC· 2024-12-17
0.765
best: 0.802 (PASDF)
SOTA
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection arXiv:2412.12617