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Models/Group3AD

Group3AD

Reported on 6 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Methodology3 results

  • Anomaly DetectiononReal 3D-AD
    Mean Performance of P. and O. · 2024-08-08
    0.743
    best: 0.821 (DUS-Net)
    SOTA
    Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningarXiv:2408.04604
  • Anomaly DetectiononReal 3D-AD
    Object AUROC· 2024-08-08
    0.751
    best: 0.802 (PASDF)
    SOTA
    Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningarXiv:2408.04604
  • Anomaly DetectiononReal 3D-AD
    Point AUROC· 2024-08-08
    0.735
    best: 0.898 (GLFM)
    SOTA
    Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningarXiv:2408.04604

Computer Vision3 results

  • 3D Anomaly DetectiononReal 3D-AD
    Mean Performance of P. and O. · 2024-08-08
    0.743
    best: 0.821 (DUS-Net)
    SOTA
    Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningarXiv:2408.04604
  • 3D Anomaly DetectiononReal 3D-AD
    Object AUROC· 2024-08-08
    0.751
    best: 0.802 (PASDF)
    SOTA
    Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningarXiv:2408.04604
  • 3D Anomaly DetectiononReal 3D-AD
    Point AUROC· 2024-08-08
    0.735
    best: 0.898 (GLFM)
    SOTA
    Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningarXiv:2408.04604