Natural image target material visual feature mapping method based on generative adversarial network

The invention provides a natural image target material visual feature mapping method based on a generative adversarial network. A deeply unsupervised learning way is used for learning the unlabeled natural image target material visual feature to obtain the high-order expression of image target material visual feature space, a mapping network about the material visual feature space between a sourcedomain image and a target domain image is learnt and established, the material visual feature of the source domain image is mapped to the material visual feature of the target domain, so that the target domain image has the material visual feature information of the source domain image, and finally, an image of which the material visual feature is mapped is obtained. The method learns from the unlabeled natural image to obtain the material visual feature information, the task target of which the material visual feature is mapped among different images is carried out, a corresponding solutionis put forward by aiming a