English

2D Image Relighting with Image-to-Image Translation

Computer Vision and Pattern Recognition 2020-06-30 v2

Abstract

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.

Keywords

Cite

@article{arxiv.2006.07816,
  title  = {2D Image Relighting with Image-to-Image Translation},
  author = {Paul Gafton and Erick Maraz},
  journal= {arXiv preprint arXiv:2006.07816},
  year   = {2020}
}

Comments

12 pages, 52 Postscript figures, uses cvpr_eso.sty eso-pic.sty ruler.sty

R2 v1 2026-06-23T16:18:28.622Z