  Modeling daytime changes in high resolution photographs, e.g., re-rendering
the same scene under different illuminations typical for day, night, or dawn,
is a challenging image manipulation task. We present the high-resolution
daytime translation (HiDT) model for this task. HiDT combines a generative
image-to-image model and a new upsampling scheme that allows to apply image
translation at high resolution. The model demonstrates competitive results in
terms of both commonly used GAN metrics and human evaluation. Importantly, this
good performance comes as a result of training on a dataset of still landscape
images with no daytime labels available. Our results are available at
https://saic-mdal.github.io/HiDT/.
