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Models/VGG16

VGG16

Reported on 25 benchmarks across 12 tasks · 1 paper · 16 SOTA

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

Computer Vision16 results

  • Depth EstimationonSiW-Enroll5
    AUC· 2014-09-04
    97.8
    best: 99.2 (ResNet18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Depth EstimationonCelebA-Spoof-Enroll5
    AUC· 2014-09-04
    98
    best: 99.2 (ResNet 18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Face ReconstructiononSiW-Enroll5
    AUC· 2014-09-04
    97.8
    best: 99.2 (ResNet18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Face ReconstructiononCelebA-Spoof-Enroll5
    AUC· 2014-09-04
    98
    best: 99.2 (ResNet 18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • 3D Face ReconstructiononSiW-Enroll5
    AUC· 2014-09-04
    97.8
    best: 99.2 (ResNet18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • 3D Face ReconstructiononCelebA-Spoof-Enroll5
    AUC· 2014-09-04
    98
    best: 99.2 (ResNet 18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Depth And Camera MotiononSiW-Enroll5
    AUC· 2014-09-04
    97.8
    best: 99.2 (ResNet18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Depth And Camera MotiononCelebA-Spoof-Enroll5
    AUC· 2014-09-04
    98
    best: 99.2 (ResNet 18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • HandonRWTH-PHOENIX Handshapes dev set
    Accuracy
    82.88
    best: 96.05 (DenseNet)
  • HandonLSA16
    Accuracy
    95.92
    best: 98.38 (Prototypical Networks + CNN)
  • Gesture RecognitiononRWTH-PHOENIX Handshapes dev set
    Accuracy
    82.88
    best: 96.05 (DenseNet)
  • Gesture RecognitiononLSA16
    Accuracy
    95.92
    best: 98.38 (Prototypical Networks + CNN)
  • Image ClassificationonRailway Track Misalignment Detection Image Dataset
    Batch Size
    128
  • Image ClassificationonRailway Track Misalignment Detection Image Dataset
    Classification Accuracy
    0.982
  • Image ClassificationonRailway Track Misalignment Detection Image Dataset
    Epochs
    5
    best: 9 (inception)
  • Image ClassificationonRailway Track Misalignment Detection Image Dataset
    Learning Rate
    0.0001

Music2 results

  • Facial Recognition and ModellingonSiW-Enroll5
    AUC· 2014-09-04
    97.8
    best: 99.2 (ResNet18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Facial Recognition and ModellingonCelebA-Spoof-Enroll5
    AUC· 2014-09-04
    98
    best: 99.2 (ResNet 18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556

Robots2 results

  • Visual OdometryonSiW-Enroll5
    AUC· 2014-09-04
    97.8
    best: 99.2 (ResNet18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Visual OdometryonCelebA-Spoof-Enroll5
    AUC· 2014-09-04
    98
    best: 99.2 (ResNet 18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556

Methodology2 results

  • 3DonSiW-Enroll5
    AUC· 2014-09-04
    97.8
    best: 99.2 (ResNet18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • 3DonCelebA-Spoof-Enroll5
    AUC· 2014-09-04
    98
    best: 99.2 (ResNet 18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556

Medical2 results

  • 3D Face ModellingonSiW-Enroll5
    AUC· 2014-09-04
    97.8
    best: 99.2 (ResNet18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • 3D Face ModellingonCelebA-Spoof-Enroll5
    AUC· 2014-09-04
    98
    best: 99.2 (ResNet 18 Personalized)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556

Natural Language Processing1 result

  • Binary ClassificationonCBIS-DDSM
    AUC
    0.6822
    best: 0.8483 (EfficientNet-B0 w/ TTA)