3DDE (Inter-pupil Norm)

Reported on 5 benchmarks across 5 tasks · 1 paper · 5 SOTA

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

Computer Vision2 results

Face ReconstructiononCOFW
Recall at 80% precision (Landmarks Visibility)· 2019-02-05
63.89
best: 72.12 (MNN+OR (Inter-pupils Norm))
SOTA
Face Alignment using a 3D Deeply-initialized Ensemble of Regression Trees arXiv:1902.01831
3D Face ReconstructiononCOFW
Recall at 80% precision (Landmarks Visibility)· 2019-02-05
63.89
best: 72.12 (MNN+OR (Inter-pupils Norm))
SOTA
Face Alignment using a 3D Deeply-initialized Ensemble of Regression Trees arXiv:1902.01831

Music1 result

Facial Recognition and ModellingonCOFW
Recall at 80% precision (Landmarks Visibility)· 2019-02-05
63.89
best: 72.12 (MNN+OR (Inter-pupils Norm))
SOTA
Face Alignment using a 3D Deeply-initialized Ensemble of Regression Trees arXiv:1902.01831

Methodology1 result

3DonCOFW
Recall at 80% precision (Landmarks Visibility)· 2019-02-05
63.89
best: 72.12 (MNN+OR (Inter-pupils Norm))
SOTA
Face Alignment using a 3D Deeply-initialized Ensemble of Regression Trees arXiv:1902.01831

Medical1 result

3D Face ModellingonCOFW
Recall at 80% precision (Landmarks Visibility)· 2019-02-05
63.89
best: 72.12 (MNN+OR (Inter-pupils Norm))
SOTA
Face Alignment using a 3D Deeply-initialized Ensemble of Regression Trees arXiv:1902.01831