The reconstruction of 3D facial model based on single face image is a challenging research direction both in the field of computer graphics and visible light imaging area,and for face recognition,facial imaging,facial animation and other practical applications are of great significance.In view of the present high computational complexity,large operation quantity,local optimal solution and poor initialization and other problems,a convolutional neural network based on the depth of single image to 3D face reconstruction algorithm is proposed in this paper.Firstly,the intensive information of the 2D face image is extracted based on the 3D transformation model,then a depth convolution neural network architecture is constructed to design an overall loss function,and to directly study of 2D face image from the pixel to the 3D coordinate mapping.Thus,the automatic construction of the 3D face model is achieved.Comparison of algorithms and simulation experiments show that the proposed algorithm in 3D face reconstruction on the normalized average error is lower,and only a 2D image face can be automatic refactoring generated 3D model face.The generated 3D model face has good robustness,accurate reconstruction,complete preservation of facial details,and good reconstruction effect for faces with different postures.It can be freely presented in three dimensional space,which will meet more practical application needs.