The invention discloses a face
image restoration method based on a generation
antagonism network. The method comprises the following steps: a face
data set is preprocessed, and a face image with a specific size is obtained by face recognition of the collected image; In the
training phase, the collected face images are used as dataset to
train the generating network and
discriminant network, aimingat obtaining more realistic images through the generating network. In order to solve the problems of
instability of training and mode collapse in the network, the least square loss is used as the
loss function of
discriminant network. In the repairing phase, a special
mask is automatically added to the original image to simulate the real missing area, and the masked face image is input into the optimized depth
convolution to generate an antagonistic network. The relevant
random parameters are obtained through context loss and two antagonistic losses, and the repairing information is obtainedthrough the generated network. The invention can not only solve the face image repairing with serious defective information, but also generate a face repairing image which is more consistent with
visual cognition.