An implementation of semantic image inpainting, using Generative Adversarial Networks that generates missing content by searching for the closest encoding of the corrupted image in the latent image manifold, given a trained generative model, by using context and prior losses. This encoding is then passed through the model to infer the missing content.
DCGAN Code from: DCGAN-tf
Dataset: Celeb-A