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Models/W-CNN He et al. (2018)

W-CNN He et al. (2018)

Reported on 30 benchmarks across 6 tasks · 1 paper · 30 SOTA

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

Computer Vision15 results

  • Face VerificationonOulu-CASIA NIR-VIS
    TAR @ FAR=0.001· 2017-08-08
    54.6
    best: 92.9 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face VerificationonOulu-CASIA NIR-VIS
    TAR @ FAR=0.01· 2017-08-08
    81.5
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face VerificationonBUAA-VisNir
    TAR @ FAR=0.001· 2017-08-08
    91.9
    best: 97.3 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face VerificationonBUAA-VisNir
    TAR @ FAR=0.01· 2017-08-08
    96
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face VerificationonCASIA NIR-VIS 2.0
    TAR @ FAR=0.001· 2017-08-08
    98.4
    best: 99.8 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face ReconstructiononOulu-CASIA NIR-VIS
    TAR @ FAR=0.001· 2017-08-08
    54.6
    best: 92.9 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face ReconstructiononOulu-CASIA NIR-VIS
    TAR @ FAR=0.01· 2017-08-08
    81.5
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face ReconstructiononBUAA-VisNir
    TAR @ FAR=0.001· 2017-08-08
    91.9
    best: 97.3 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face ReconstructiononBUAA-VisNir
    TAR @ FAR=0.01· 2017-08-08
    96
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Face ReconstructiononCASIA NIR-VIS 2.0
    TAR @ FAR=0.001· 2017-08-08
    98.4
    best: 99.8 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ReconstructiononOulu-CASIA NIR-VIS
    TAR @ FAR=0.001· 2017-08-08
    54.6
    best: 92.9 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ReconstructiononOulu-CASIA NIR-VIS
    TAR @ FAR=0.01· 2017-08-08
    81.5
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ReconstructiononBUAA-VisNir
    TAR @ FAR=0.001· 2017-08-08
    91.9
    best: 97.3 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ReconstructiononBUAA-VisNir
    TAR @ FAR=0.01· 2017-08-08
    96
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ReconstructiononCASIA NIR-VIS 2.0
    TAR @ FAR=0.001· 2017-08-08
    98.4
    best: 99.8 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412

Music5 results

  • Facial Recognition and ModellingonOulu-CASIA NIR-VIS
    TAR @ FAR=0.001· 2017-08-08
    54.6
    best: 92.9 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Facial Recognition and ModellingonOulu-CASIA NIR-VIS
    TAR @ FAR=0.01· 2017-08-08
    81.5
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Facial Recognition and ModellingonBUAA-VisNir
    TAR @ FAR=0.001· 2017-08-08
    91.9
    best: 97.3 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Facial Recognition and ModellingonBUAA-VisNir
    TAR @ FAR=0.01· 2017-08-08
    96
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • Facial Recognition and ModellingonCASIA NIR-VIS 2.0
    TAR @ FAR=0.001· 2017-08-08
    98.4
    best: 99.8 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412

Methodology5 results

  • 3DonOulu-CASIA NIR-VIS
    TAR @ FAR=0.001· 2017-08-08
    54.6
    best: 92.9 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3DonOulu-CASIA NIR-VIS
    TAR @ FAR=0.01· 2017-08-08
    81.5
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3DonBUAA-VisNir
    TAR @ FAR=0.001· 2017-08-08
    91.9
    best: 97.3 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3DonBUAA-VisNir
    TAR @ FAR=0.01· 2017-08-08
    96
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3DonCASIA NIR-VIS 2.0
    TAR @ FAR=0.001· 2017-08-08
    98.4
    best: 99.8 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412

Medical5 results

  • 3D Face ModellingonOulu-CASIA NIR-VIS
    TAR @ FAR=0.001· 2017-08-08
    54.6
    best: 92.9 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ModellingonOulu-CASIA NIR-VIS
    TAR @ FAR=0.01· 2017-08-08
    81.5
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ModellingonBUAA-VisNir
    TAR @ FAR=0.001· 2017-08-08
    91.9
    best: 97.3 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ModellingonBUAA-VisNir
    TAR @ FAR=0.01· 2017-08-08
    96
    best: 98.5 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412
  • 3D Face ModellingonCASIA NIR-VIS 2.0
    TAR @ FAR=0.001· 2017-08-08
    98.4
    best: 99.8 (LightCNN-29 + DVG)
    SOTA
    Wasserstein CNN: Learning Invariant Features for NIR-VIS Face RecognitionarXiv:1708.02412