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Models/DeepGCN

DeepGCN

Reported on 16 benchmarks across 7 tasks · 1 paper · 6 SOTA

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

Computer Vision7 results

  • Shape Representation Of 3D Point CloudsonModelNet40
    Overall Accuracy· 2019-10-15
    93.6
    best: 95.3 (PointGST)
    SOTA
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • 3D Semantic SegmentationonPartNet
    mIOU· 2019-10-15
    45.1
    best: 62.1 (CSN)
    SOTA
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • 3D Point Cloud ClassificationonModelNet40
    Overall Accuracy· 2019-10-15
    93.6
    best: 95.3 (PointGST)
    SOTA
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • 3D Point Cloud ReconstructiononModelNet40
    Overall Accuracy· 2019-10-15
    93.6
    best: 95.3 (PointGST)
    SOTA
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • Shape Representation Of 3D Point CloudsonModelNet40
    Mean Accuracy· 2019-10-15
    90.9
    best: 92.4 (ULIP + PointMLP)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • 3D Point Cloud ClassificationonModelNet40
    Mean Accuracy· 2019-10-15
    90.9
    best: 92.4 (ULIP + PointMLP)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • 3D Point Cloud ReconstructiononModelNet40
    Mean Accuracy· 2019-10-15
    90.9
    best: 92.4 (ULIP + PointMLP)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849

Medical4 results

  • Semantic SegmentationonPartNet
    mIOU· 2019-10-15
    45.1
    best: 62.1 (CSN)
    SOTA
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • Semantic SegmentationonS3DIS Area5
    mIoU· 2019-10-15
    52.49
    best: 76 (Sonata + PTv3)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • Semantic SegmentationonS3DIS
    Mean IoU· 2019-10-15
    60
    best: 82.3 (Sonata + PTv3)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • Semantic SegmentationonS3DIS
    oAcc· 2019-10-15
    85.9
    best: 93.3 (Sonata + PTv3)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849

Audio4 results

  • 10-shot image generationonPartNet
    mIOU· 2019-10-15
    45.1
    best: 62.1 (CSN)
    SOTA
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • 10-shot image generationonS3DIS Area5
    mIoU· 2019-10-15
    52.49
    best: 76 (Sonata + PTv3)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • 10-shot image generationonS3DIS
    Mean IoU· 2019-10-15
    60
    best: 82.3 (Sonata + PTv3)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849
  • 10-shot image generationonS3DIS
    oAcc· 2019-10-15
    85.9
    best: 93.3 (Sonata + PTv3)
    DeepGCNs: Making GCNs Go as Deep as CNNsarXiv:1910.06849

Graphs1 result

  • Node Property Predictiononogbn-proteins
    Number of params
    2374456
    best: 664233700 (LD+GAT)