Abstract: Sketch face synthesis technology plays an important role in different fields. The sharpness of the face contour generated by the traditional sketch face synthesis method is insufficient, the texture is blurred, and the details of face features inside the contour are missing. At the same time, there are obvious rough pixels in the image. To solve the above problems, a generative adversarial network model based on feature filtering is proposed. This model extracted the features of different levels of faces to enriches the feature details, improved the appearance contour and texture expression of faces through the appearance filtering and texture processing module, and reduced the rough pixels in the image through the total variation loss function, thus improving the overall clarity of the image. Experiments on the CUFS and CUFSF face datasets prove the effectiveness of this method in enriching face features, improving texture details, and reducing image rough pixels.