GAN Based Image Inpainting Methods: A Taxonomy

Abstract

Image inpainting is the technique that's able to “repair” or “correct” the image by reconstructing missing regions of an image using AI algorithms. As the techniques of images inpainting become mature in recent years, the demand for image inpainting algorithms rises in the market. It can be used to fill out missing areas in a picture, denoise images, or even remove a specific object from an image. To this end, it is important to propose a survey for image inpainting method, which can provide a comprehensive introduction of this area. The reason for creating this paper is due to the lack of resources that conclude all the methods that are being used in image inpainting. As the field of image inpainting soars, researchers may need documents which explain all the methods that can be used to train their image inpainting models. In the paper, we gathered some most successful methods that are used by many researchers. We explained their model, methods they used, the results of the training, and the advantages of the approaches they used in their research.