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Models/D3Feat-pred

D3Feat-pred

Reported on 8 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.

Computer Vision8 results

  • Point Cloud Registrationon3DMatch (trained on KITTI)
    Recall· 2020-03-06
    0.627
    best: 0.922 (GeDi)
    SOTA
    D3Feat: Joint Learning of Dense Detection and Description of 3D Local FeaturesarXiv:2003.03164
  • Point Cloud RegistrationonKITTI (trained on 3DMatch)
    Success Rate· 2020-03-06
    36.76
    best: 98.92 (GeDi)
    SOTA
    D3Feat: Joint Learning of Dense Detection and Description of 3D Local FeaturesarXiv:2003.03164
  • Point Cloud RegistrationonKITTI
    Success Rate· 2020-03-06
    99.81
    best: 99.82 (GeDi)
    SOTA
    D3Feat: Joint Learning of Dense Detection and Description of 3D Local FeaturesarXiv:2003.03164
  • 3D Point Cloud Interpolationon3DMatch (trained on KITTI)
    Recall· 2020-03-06
    0.627
    best: 0.922 (GeDi)
    SOTA
    D3Feat: Joint Learning of Dense Detection and Description of 3D Local FeaturesarXiv:2003.03164
  • 3D Point Cloud InterpolationonKITTI (trained on 3DMatch)
    Success Rate· 2020-03-06
    36.76
    best: 98.92 (GeDi)
    SOTA
    D3Feat: Joint Learning of Dense Detection and Description of 3D Local FeaturesarXiv:2003.03164
  • 3D Point Cloud InterpolationonKITTI
    Success Rate· 2020-03-06
    99.81
    best: 99.82 (GeDi)
    SOTA
    D3Feat: Joint Learning of Dense Detection and Description of 3D Local FeaturesarXiv:2003.03164
  • Point Cloud RegistrationonETH (trained on 3DMatch)
    Feature Matching Recall· 2020-03-06
    0.563
    best: 0.982 (GeDi)
    D3Feat: Joint Learning of Dense Detection and Description of 3D Local FeaturesarXiv:2003.03164
  • 3D Point Cloud InterpolationonETH (trained on 3DMatch)
    Feature Matching Recall· 2020-03-06
    0.563
    best: 0.982 (GeDi)
    D3Feat: Joint Learning of Dense Detection and Description of 3D Local FeaturesarXiv:2003.03164