  It this paper we revisit the fast stylization method introduced in Ulyanov
et. al. (2016). We show how a small change in the stylization architecture
results in a significant qualitative improvement in the generated images. The
change is limited to swapping batch normalization with instance normalization,
and to apply the latter both at training and testing times. The resulting
method can be used to train high-performance architectures for real-time image
generation. The code will is made available on github at
https://github.com/DmitryUlyanov/texture_nets. Full paper can be found at
arXiv:1701.02096.
