Abstract: In view of the localized facial contour features, combining with the extraction of key feature points and the fusion of adjacent color regions of the face, we presented a CycleGAN-based local facial stylization generation algorithm, and constructed the deep learning network with the attention mechanism to generate the local facial cartoon stylization. The sample facial images were marked by using the local area binarization method to constrain the key features and points. In order to naturally match the generated image with the extracted features, the mean filtering operation was utilized to smooth and feather the edge contour of the extracted region. Finally, the generative adversarial networks (GAN) network was constructed, and the training data set was employed to generate cartoon stylization images in the local contour feature area of facial images. The experiment results show that the presented algorithm exhibits high robustness for generating facial stylization, and that it can be applied to the generation of stylized facial images of various scales. 

Key words:  , facial features, local area, generative adversarial networks, stylization