DE-GAN: Domain Embedded GAN for High Quality Face Image Inpainting

•DE-GAN incorporates an HVAE in the generator to embed three types of face domain information into latent variables as the guidance for face inpainting, which produces more natural faces.•Different from existing multiple stage training methods that use prior information to complete image or face inpainting, our proposed method is end-to-end trainable.•To the best of our knowledge, our work is the first on the evaluation of the large pose side face inpainting problem. Our inpainting method achieves the state-of-the-art visual quality and facial structures for inpainting under-pose variations.