While makeup virtual-try-on is now widespread, parametrizing a computer graphics rendering engine for synthesizing images of a given cosmetics product remains a challenging task.
We also provide a postprocessing and rendering algorithm for nail polish try-on, which integrates with our semantic segmentation and fingernail base-tip direction predictions.
Recent works on convolutional neural networks (CNNs) for facial alignment have demonstrated unprecedented accuracy on a variety of large, publicly available datasets.
At an average normalized error of e < 0. 05, the regressor trained on manually annotated data yields an accuracy of 95. 07% (BioID), 99. 27% (GI4E), and 95. 68% (TalkingFace).