Research on 3D Face Sparse Reconstruction Based on Deep Learning
In order to improve the accuracy of 3D face sparse reconstruction,referring to the point cloud feature extraction net-work in the field of deep learning,a new face landmarks feature extraction network is established.This work overcomes the disadvan-tage that the traditional projection reconstruction method can only fit on 2D plane.It directly extracts global features from the input 3D sparse landmarks and converts them into the required face model parameters to realize the reconstruction process from sparse landmarks to 3D face.The experimental results show that the reconstruction accuracy of the method on BFM 3D face database is sig-nificantly better than the traditional projection reconstruction method,and has desirable performance.
deep learning3D facesparse reconstructionmorphable modelfeature extraction
万方数据
维普
