The generator network (F2P) used here is made up of three major convolution blocks. The first one finds an encoding of Fortnite screenshot in a lower dimensional latent space. This encoding is transformed into an encoding that represents PUBG in that same latent space. The decoder then constructs the output image from the transformed encoding, giving us the image of Fortnite that looks like PUBG.

One limitation I faced during this training process was that I could only work with 256x256 images due to GPU memory limitations. This significantly affects the results, but if you have more video memory than 8gb, you could try to generate up to 512x512 images. If you are able to, please let me know here!

Results

The generated images from CycleGAN after 12 hours of training seem very promising. The network was able to successfully convert colors of the sky, the trees and the grass from Fortnite to that of PUBG. The over-saturated colors of Fortnite were transformed into the more realistic colors of PUBG.

The sky looks less bluish and the cartoonish greens of the grass and the trees look much closer to those seen in PUBG. It even learnt to replace the health meter at the bottom of the screen with the gun and ammo indicator of PUBG! What it was unable to link in the two domains was the appearance of the player, which is why the pixels around it are kind-of blurry. Overall, the network did a decent job of identifying objects across the two domains and transforming their appearance.

To view longer results, please view the video embedded below. If you like what you see, don’t forget to click here and subscribe to my YouTube channel!

Application to graphic mods in games

While the results look really good to me, it is clear that we still have a long way to go before I can actually play Fortnite with PUBG graphics. But once we are able to generate higher resolution images in real time using these networks, it could become possible in the future to build graphic mod engines for games without having to rely on the game developers. We could use the visual style of a game of our liking and apply it to any other game!