  We tackle the problem of texture synthesis in the setting where many input
images are given and a large-scale output is required. We build on recent
generative adversarial networks and propose two extensions in this paper.
First, we propose an algorithm to combine outputs of GANs trained on a smaller
resolution to produce a large-scale plausible texture map with virtually no
boundary artifacts. Second, we propose a user interface to enable artistic
control. Our quantitative and qualitative results showcase the generation of
synthesized high-resolution maps consisting of up to hundreds of megapixels as
a case in point.
