A method for 3D reconstruction and texture generation from single-view face based on multi-task learning
A multi-task learning and 3D reconstruction technology, which is applied in the field of single-view face 3D reconstruction and texture generation based on multi-task learning, can solve problems such as inconvenience, texture errors and limitations in occluded areas, and achieve convenient post-processing and data generation Comprehensive, Fast Effects
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[0072] This embodiment provides a method for single-view face 3D reconstruction and texture generation based on multi-task learning, specifically including:
[0073] (1) In order to use the 300W_LP face database to make a data set, first restore the grid structure of the 3D model of the face from the geometric shape parameters in the 3DMM model parameters corresponding to the face images in the natural scene, and then use the 3DMM model parameters The texture parameters in the method and the additional light source parameters restore the texture information of the 3D model of the face. The 300W_LP face database includes four sub-datasets of AFW, HELEN, IBUG, and LFPW, which contain 3837 faces of different identities. At the same time, the faces of each identity have images from different angles, including images from the left side to the middle of the right side Insert images with a number of viewpoints ranging from 9 to 17. They all correspond to the 3D model of the face of ...
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