Semantic Image Inpainting with Deep Generative Models
Words: 959 Pages: 3 4244Abstract Semantic image inpainting is a challenging task?Traditional methods do not recover images well due to the lack of high level context. So we propose a novel method for semantic image inpainting, which generates the missing content by conditioning on the available data. We use Deep Convolution Generative Adversarial Networks (DCGAN) to train a generated model, and then input the code containing the prior information into the model to get the inpainting image. We successfully implemented image restoration on three […]