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Models/KDN

KDN

Reported on 40 benchmarks across 5 tasks

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

Computer Vision16 results

  • Face Reconstructionon300W Split 2 (300W-LP)
    AUC@7 (bbox)
    68.3
    best: 71.1 (SH-FAN)
  • Face Reconstructionon300W Split 2 (300W-LP)
    NME (bbox)
    2.21
    best: 2.32 (2D-FAN)
  • Face ReconstructiononCOFW-68 (300WLP)
    AUC@7
    60.1
    best: 64.9 (SH-FAN)
  • Face ReconstructiononCOFW-68 (300WLP)
    NME (box)
    2.73
    best: 2.95 (2D-FAN)
  • Face Reconstructionon300W Split 2
    AUC@7 (box)
    67.3
    best: 71 (SPIGA)
  • Face Reconstructionon300W Split 2
    NME (box)
    2.49
  • Face ReconstructiononAFLW-19
    AUC_box@0.07 (%, Full)
    60.3
    best: 81.8 (FiFA)
  • Face ReconstructiononAFLW-19
    NME_box (%, Full)
    2.8
    best: 4.04 (SAN)
  • 3D Face ReconstructiononCOFW-68 (300WLP)
    AUC@7
    60.1
    best: 64.9 (SH-FAN)
  • 3D Face ReconstructiononCOFW-68 (300WLP)
    NME (box)
    2.73
    best: 2.95 (2D-FAN)
  • 3D Face Reconstructionon300W Split 2 (300W-LP)
    AUC@7 (bbox)
    68.3
    best: 71.1 (SH-FAN)
  • 3D Face Reconstructionon300W Split 2 (300W-LP)
    NME (bbox)
    2.21
    best: 2.32 (2D-FAN)
  • 3D Face ReconstructiononAFLW-19
    AUC_box@0.07 (%, Full)
    60.3
    best: 81.8 (FiFA)
  • 3D Face ReconstructiononAFLW-19
    NME_box (%, Full)
    2.8
    best: 4.04 (SAN)
  • 3D Face Reconstructionon300W Split 2
    AUC@7 (box)
    67.3
    best: 71 (SPIGA)
  • 3D Face Reconstructionon300W Split 2
    NME (box)
    2.49

Music8 results

  • Facial Recognition and ModellingonCOFW-68 (300WLP)
    AUC@7
    60.1
    best: 64.9 (SH-FAN)
  • Facial Recognition and ModellingonCOFW-68 (300WLP)
    NME (box)
    2.73
    best: 2.95 (2D-FAN)
  • Facial Recognition and Modellingon300W Split 2 (300W-LP)
    AUC@7 (bbox)
    68.3
    best: 71.1 (SH-FAN)
  • Facial Recognition and Modellingon300W Split 2 (300W-LP)
    NME (bbox)
    2.21
    best: 2.32 (2D-FAN)
  • Facial Recognition and ModellingonAFLW-19
    AUC_box@0.07 (%, Full)
    60.3
    best: 81.8 (FiFA)
  • Facial Recognition and ModellingonAFLW-19
    NME_box (%, Full)
    2.8
    best: 4.04 (SAN)
  • Facial Recognition and Modellingon300W Split 2
    AUC@7 (box)
    67.3
    best: 71 (SPIGA)
  • Facial Recognition and Modellingon300W Split 2
    NME (box)
    2.49

Methodology8 results

  • 3Don300W Split 2 (300W-LP)
    AUC@7 (bbox)
    68.3
    best: 71.1 (SH-FAN)
  • 3Don300W Split 2 (300W-LP)
    NME (bbox)
    2.21
    best: 2.32 (2D-FAN)
  • 3DonCOFW-68 (300WLP)
    AUC@7
    60.1
    best: 64.9 (SH-FAN)
  • 3DonCOFW-68 (300WLP)
    NME (box)
    2.73
    best: 2.95 (2D-FAN)
  • 3Don300W Split 2
    AUC@7 (box)
    67.3
    best: 71 (SPIGA)
  • 3Don300W Split 2
    NME (box)
    2.49
  • 3DonAFLW-19
    AUC_box@0.07 (%, Full)
    60.3
    best: 81.8 (FiFA)
  • 3DonAFLW-19
    NME_box (%, Full)
    2.8
    best: 4.04 (SAN)

Medical8 results

  • 3D Face ModellingonCOFW-68 (300WLP)
    AUC@7
    60.1
    best: 64.9 (SH-FAN)
  • 3D Face ModellingonCOFW-68 (300WLP)
    NME (box)
    2.73
    best: 2.95 (2D-FAN)
  • 3D Face Modellingon300W Split 2 (300W-LP)
    AUC@7 (bbox)
    68.3
    best: 71.1 (SH-FAN)
  • 3D Face Modellingon300W Split 2 (300W-LP)
    NME (bbox)
    2.21
    best: 2.32 (2D-FAN)
  • 3D Face ModellingonAFLW-19
    AUC_box@0.07 (%, Full)
    60.3
    best: 81.8 (FiFA)
  • 3D Face ModellingonAFLW-19
    NME_box (%, Full)
    2.8
    best: 4.04 (SAN)
  • 3D Face Modellingon300W Split 2
    AUC@7 (box)
    67.3
    best: 71 (SPIGA)
  • 3D Face Modellingon300W Split 2
    NME (box)
    2.49