
GauGAN Turns Doodles into Stunning, Photorealistic Landscapes - vadansky
https://blogs.nvidia.com/blog/2019/03/18/gaugan-photorealistic-landscapes-nvidia-research/
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MayeulC
This is a very interesting use of the technology, which I hadn't thought of
before.

I would really like to see the tool open-sourced. I guess that re-training the
networks on a custom dataset could quickly lead to some interesting results.
Even in its current incarnation, the tool could be quite entertaining.

It might also be interesting to apply the methods here to 3D environments,
which are typically designed with placeholder objects and textures. I wouldn't
be surprised if this were to be applied in videogames to save both on
development time (art costs), and file size (multi-gigabyte texture files
seems to be quite common), as a complement to procedural generation.

Given nVidia's recent publications [1] on this topic, it seems like they are
not too far away from offering that kind of facilities to partner game
developers.

Also of interest related to this software:
[https://nvlabs.github.io/SPADE/](https://nvlabs.github.io/SPADE/)
[https://github.com/NVlabs/SPADE](https://github.com/NVlabs/SPADE)

[1]: I'm mainly thinking of [https://www.lyrn.ai/2018/12/26/a-style-based-
generator-archi...](https://www.lyrn.ai/2018/12/26/a-style-based-generator-
architecture-for-generative-adversarial-networks/)

