SEGAN

SEGAN is a novel diversity-generated image inpainting adversarial network with a newly designed style extractor for diversity image inpainting tasks. For a single input image with missing regions, our model can generate numerous diverse results with plausible content. Experiments on various datasets have shown that our results are diverse and natural, especially for images with large missing areas.