The invention discloses a method for realizing facial expression migration of a cyclic generative adversarial network based on spectrum normalization, which comprises the following steps of: S1, collecting various facial expression pictures, and classifying the facial expression pictures one by one according to facial expressions; S2, preprocessing the pictures, removing blurred pictures, obtaining five key points of the human face by using a human face detection algorithm, and uniformly cutting face pictures according to the key points; S3, constructing a cyclic generative adversarial networkconsisting of a generator and a discriminator, respectively inputting the two types of preprocessed pictures into the network to calculate a loss function, and training the loss function; and S4, obtaining the trained generator as a tool for human face expression migration, and applying the trained generator to actual measurement. The cyclic generative adversarial network based on spectrum normalization can enable one generator to realize migration of multiple facial expressions, and the generated facial expressions can be more natural and have better robustness.