A standard face generation method based on a generative adversarial mechanism and an attention mechanism

The invention discloses a standard face generation method based on a generative adversarial mechanism and an attention mechanism, and the method comprises the steps: a data set design step: building face codes with a plurality of non-limiting factors for a face image according to the related annotation data of a database, and enabling the codes and the face image to serve as the input of a model;A model design and training step: designing a corresponding network structure by utilizing a generative adversarial mechanism and an attention mechanism, and carrying out model training by utilizing the constructed data pair so as to obtain a network model weight; And a model prediction step: predicting the acquired face image through the model. According to the invention, a deep learning networktechnology is applied to standard face generation to generate color, forward and normal illumination standard face images; An accurate standard front face image can be obtained through a deep learningnetwork method, the matchi