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GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
[article]
2019
arXiv
pre-print
In the past few years, a lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of Deep Convolutional Neural Networks (DCNNs). In the most recent works, differentiable renderers were employed in order to learn the relationship between the facial identity features and the parameters of a 3D morphable model for shape and texture. The texture features either correspond to components of a linear texture space or are learned by
arXiv:1902.05978v2
fatcat:uw2gxh3onbdzzaogl44ivjq3ja