How to create realistic Grand Theft Auto 5 graphics with Deep Learning

For the first task, I have taken screenshots of the game as our source domain which we want to convert into something photo-realistic. The target domain comes from the cityscapes dataset that represents the real world (which we aim to make our game resemble). Based on about three days of training for about 100 epochs, the Cyclegan model seems to do a very nice job of adapting GTA to the real world domain. I really like how the smaller details are not lost in this translation and the image retains its sharpness even at such a low resolution. The main downside is that this neural network turned out to be quite materialistic: it hallucinates a Mercedes logo everywhere, ruining the almost perfect conversion from GTA to real world.