Accurate facial computer vision with Microsoft system trained only on artificial images
Accurate facial computer vision with Microsoft system trained only on artificial images
Fake It Till You Make It: Face analysis in the wild using synthetic data alone
arXiv paper abstract https://arxiv.org/abs/2109.15102
arXiv PDF paper https://arxiv.org/pdf/2109.15102.pdf
Project page https://microsoft.github.io/FaceSynthetics
... demonstrate that it is possible to perform face-related computer vision in the wild using synthetic data alone.
The community has long enjoyed the benefits of synthesizing training data with graphics, but the domain gap between real and synthetic data has remained a problem, especially for human faces.
... show that it is possible to synthesize data with minimal domain gap, so that models trained on synthetic data generalize to real in-the-wild datasets.
... combine a procedurally-generated parametric 3D face model with a comprehensive library of hand-crafted assets to render training images with unprecedented realism and diversity.
... train machine learning systems for face-related tasks such as landmark localization and face parsing,
showing that synthetic data can both match real data in accuracy as well as open up new approaches where manual labelling would be impossible.
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