An interactive face cartoon method based on generative adversarial networks

Abstract

The invention discloses an interactive face cartoon method based on generative adversarial networks. The image to be processed is firstly subjected to interactive segmentation processing to obtain eyebrow-eye, mouth-nose, hair and face images, and then eyebrow-eye, mouth-nose and hair images are respectively input into three trained eye, mouth-nose and hair generation models to output corresponding cartoon five-feature images. Based on the cartoon processing of face image, the cartoon face can be obtained directly. Then the facial features are synthesized on the cartoon face and superimposed on the hair effect to get the final cartoon image. The invention utilizes the advantages of interactive and generating antagonistic network, obtains the five features of human hair, face shape and facethrough interactive segmentation, eliminates the difference between training samples due to different backgrounds, converts the style of each part through generating antagonistic network, and retainsas much information of eye corner, mouth corner and other detail parts as possible.

Description

technical field [0001] The invention belongs to the technical field of image processing and computer vision, and relates to an interactive face cartoon method based on a generative confrontation network. Background technique [0002] In recent years, with the rapid development of mobile networks and mobile phones, especially the vigorous development of mobile Internet, digital entertainment has become larger and larger in the industry with its special advantages, and the technology of face cartoon drawing has emerged as the times require. This technology is mainly Using image processing and computer programs to automatically generate cartooning results can greatly reduce the workload of painters and improve the efficiency of cartooning. [0003] At present, the face cartoonization methods mainly include interactive methods and unsupervised learning methods. The interactive-based method uses human-computer interaction to extract the contour lines of the face, and then artifi...

AI Technical Summary

Problems solved by technology

Based on this principle, the generative confrontation network is widely used in image generation and style transfer. Compared with the general generation model, the network can generate clearer images, but the details are still insufficient, and it relies on a large number of training samples with similar styles.

Images