Semantic-Image-Inpainting

Simplely implement the paper 'Semantic Image Inpainting with Deep Generative Models'

Indroduction

This code simplely implement the paper Semantic Image Inpainting with Deep Generative Models. The results of the paper have good results of face inpainting.

Method

The method of the paper is divided into two stages,

First, train the DCGAN to get the pretrained model(generator, discriminator).

Second, use the pretrained model of DCGAN from the first stage to train the input(z) of the generator, a little similar with neural style transfer.

Python packages

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tensorflow 1.4.0

python 3.5

pillow

numpy

scipy

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Dataset

In the first stage, we select the CelebA as the dataset of the DCGAN to get the pretrained model, and remain 1000 as test data in the second stage.

Results

Raw	incompleted	completed

Inpainting

col 1: raw image, col 2: incompleted image, col 3: generated image by generator, col 4: completed image