  With the advent of Generative Adversarial Networks (GANs), a finer level of
control in manipulating various features of an image has become possible. One
example of such fine manipulation is changing the position of the light source
in a scene. This is fundamentally an ill-posed problem, since it requires
understanding the scene geometry to generate proper lighting effects. This
problem is not a trivial one and can become even more complicated if we want to
change the direction of the light source from any direction to a specific one.
Here we provide our attempt to solve this problem using GANs. Specifically,
pix2pix [arXiv:1611.07004] trained with the dataset VIDIT [arXiv:2005.05460]
which contains images of the same scene with different types of light
temperature and 8 different light source positions (N, NE, E, SE, S, SW, W,
NW). The results are 8 neural networks trained to be able to change the
direction of the light source from any direction to one of the 8 previously
mentioned. Additionally, we provide, as a tool, a simple CNN trained to
identify the direction of the light source in an image.
