  Since its appearance, Generative Adversarial Networks (GANs) have received a
lot of interest in the AI community. In image generation several projects
showed how GANs are able to generate photorealistic images but the results so
far did not look adequate for the quality standard of visual media production
industry. We present an optimized image generation process based on a Deep
Convolutional Generative Adversarial Networks (DCGANs), in order to create
photorealistic high-resolution images (up to 1024x1024 pixels). Furthermore,
the system was fed with a limited dataset of images, less than two thousand
images. All these results give more clue about future exploitation of GANs in
Computer Graphics and Visual Effects.
