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Models/CrossMoCo

CrossMoCo

Reported on 47 benchmarks across 7 tasks

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

Computer Vision45 results

  • Shape Representation Of 3D Point CloudsonModelNet40
    Overall Accuracy
    91.49
    best: 95.3 (PointGST)
  • Shape Representation Of 3D Point CloudsonModelNet40
    Classification Accuracy
    91.49
    best: 93.6 (Ours)
  • Shape Representation Of 3D Point CloudsonModelNet40 10-way (20-shot)
    Overall Accuracy
    91
    best: 96.5 (ReCon++)
  • Shape Representation Of 3D Point CloudsonModelNet40 10-way (20-shot)
    Standard Deviation
    3.4
    best: 13.5 (PointNet)
  • Shape Representation Of 3D Point CloudsonScanObjectNN 5-way (10-shot)
    Overall Accuracy
    84
  • Shape Representation Of 3D Point CloudsonModelNet40 5-way (10-shot)
    Overall Accuracy
    93.8
    best: 98 (PointGPT)
  • Shape Representation Of 3D Point CloudsonModelNet40 5-way (10-shot)
    Standard Deviation
    4.5
    best: 16 (PointNet++)
  • Shape Representation Of 3D Point CloudsonScanObjectNN 10-way (10-shot)
    Overall Accuracy
    69.6
  • Shape Representation Of 3D Point CloudsonScanObjectNN 5-way (20-shot)
    Overall Accuracy
    87.6
  • Shape Representation Of 3D Point CloudsonModelNet40 10-way (10-shot)
    Overall Accuracy
    88.7
    best: 95 (Point-JEPA)
  • Shape Representation Of 3D Point CloudsonModelNet40 10-way (10-shot)
    Standard Deviation
    3.9
    best: 13.5 (PointNet)
  • Shape Representation Of 3D Point CloudsonScanObjectNN 10-way (20-shot)
    Overall Accuracy
    78.1
  • Shape Representation Of 3D Point CloudsonModelNet40 5-way (20-shot)
    Overall Accuracy
    96.8
    best: 99.5 (ReCon++)
  • Shape Representation Of 3D Point CloudsonModelNet40 5-way (20-shot)
    Standard Deviation
    1.7
    best: 15.5 (PointNet)
  • 3D Object ClassificationonModelNet40
    Classification Accuracy
    91.49
    best: 93.6 (Ours)
  • 3D Point Cloud ClassificationonModelNet40
    Overall Accuracy
    91.49
    best: 95.3 (PointGST)
  • 3D Point Cloud ClassificationonModelNet40
    Classification Accuracy
    91.49
    best: 93.6 (Ours)
  • 3D Point Cloud ClassificationonModelNet40 10-way (20-shot)
    Overall Accuracy
    91
    best: 96.5 (ReCon++)
  • 3D Point Cloud ClassificationonModelNet40 10-way (20-shot)
    Standard Deviation
    3.4
    best: 13.5 (PointNet)
  • 3D Point Cloud ClassificationonScanObjectNN 5-way (10-shot)
    Overall Accuracy
    84
  • 3D Point Cloud ClassificationonModelNet40 5-way (10-shot)
    Overall Accuracy
    93.8
    best: 98 (PointGPT)
  • 3D Point Cloud ClassificationonModelNet40 5-way (10-shot)
    Standard Deviation
    4.5
    best: 16 (PointNet++)
  • 3D Point Cloud ClassificationonScanObjectNN 10-way (10-shot)
    Overall Accuracy
    69.6
  • 3D Point Cloud ClassificationonScanObjectNN 5-way (20-shot)
    Overall Accuracy
    87.6
  • 3D Point Cloud ClassificationonModelNet40 10-way (10-shot)
    Overall Accuracy
    88.7
    best: 95 (Point-JEPA)
  • 3D Point Cloud ClassificationonModelNet40 10-way (10-shot)
    Standard Deviation
    3.9
    best: 13.5 (PointNet)
  • 3D Point Cloud ClassificationonScanObjectNN 10-way (20-shot)
    Overall Accuracy
    78.1
  • 3D Point Cloud ClassificationonModelNet40 5-way (20-shot)
    Overall Accuracy
    96.8
    best: 99.5 (ReCon++)
  • 3D Point Cloud ClassificationonModelNet40 5-way (20-shot)
    Standard Deviation
    1.7
    best: 15.5 (PointNet)
  • 3D Point Cloud Linear ClassificationonModelNet40
    Overall Accuracy
    91.49
    best: 93.6 (ReCon++)
  • 3D Point Cloud Linear ClassificationonScanObjectNN
    Overall Accuracy
    86.06
  • 3D Point Cloud ReconstructiononModelNet40
    Overall Accuracy
    91.49
    best: 95.3 (PointGST)
  • 3D Point Cloud ReconstructiononModelNet40
    Classification Accuracy
    91.49
    best: 93.6 (Ours)
  • 3D Point Cloud ReconstructiononModelNet40 10-way (20-shot)
    Overall Accuracy
    91
    best: 96.5 (ReCon++)
  • 3D Point Cloud ReconstructiononModelNet40 10-way (20-shot)
    Standard Deviation
    3.4
    best: 13.5 (PointNet)
  • 3D Point Cloud ReconstructiononScanObjectNN 5-way (10-shot)
    Overall Accuracy
    84
  • 3D Point Cloud ReconstructiononModelNet40 5-way (10-shot)
    Overall Accuracy
    93.8
    best: 98 (PointGPT)
  • 3D Point Cloud ReconstructiononModelNet40 5-way (10-shot)
    Standard Deviation
    4.5
    best: 16 (PointNet++)
  • 3D Point Cloud ReconstructiononScanObjectNN 10-way (10-shot)
    Overall Accuracy
    69.6
  • 3D Point Cloud ReconstructiononScanObjectNN 5-way (20-shot)
    Overall Accuracy
    87.6
  • 3D Point Cloud ReconstructiononModelNet40 10-way (10-shot)
    Overall Accuracy
    88.7
    best: 95 (Point-JEPA)
  • 3D Point Cloud ReconstructiononModelNet40 10-way (10-shot)
    Standard Deviation
    3.9
    best: 13.5 (PointNet)
  • 3D Point Cloud ReconstructiononScanObjectNN 10-way (20-shot)
    Overall Accuracy
    78.1
  • 3D Point Cloud ReconstructiononModelNet40 5-way (20-shot)
    Overall Accuracy
    96.8
    best: 99.5 (ReCon++)
  • 3D Point Cloud ReconstructiononModelNet40 5-way (20-shot)
    Standard Deviation
    1.7
    best: 15.5 (PointNet)

Methodology1 result

  • 3DonModelNet40
    Classification Accuracy
    91.49
    best: 93.6 (Ours)

Medical1 result

  • 3D ClassificationonModelNet40
    Classification Accuracy
    91.49
    best: 93.6 (Ours)