Detail Reconstruction of 3D Face Model from Single Image
Hongxin Xu, Ruoming Lan, Tianping Li · Journal of Physics Conference Series · 2021
Abstract With the development of computer vision technology, 3D face model reconstruction technology has a great breakthrough. In view of the current popular deep learning method, we use an algorithm based on neural network to restore the details of 3D face model. We design a high frequency detail generation network to generate displacement map based on the texture extracted from the original image. The displacement map contains a large number of high frequency detail features of the target face. By embedding the displacement map into the face model, the details of the model can be restored.