Project

Understanding Light via Deep Neural Networks

Our goal is to understand the illumination of an environment. By disentangling the illumination effect from other intrinsic properties (e.g. geometry, texture, color), we can better understand how human perceive the world. It also has several applications such as single image relighting, color editing, etc.

Our goal is to recover the illumination of an environment from a single image. In particular, we are interested in detecting the light sources, learning the contribution of each light source to each pixel, etc. Current publicly available datasets, however, are either small, synthetic, or sparsely annotated. Instead of relying on those data and directly training a fully supervised model, we take a different route and aim to recover the intrinsic properties of an image with very weak/no supervision.

Group

Vision Group
Contact us

If you would like to contact us about our work, please refer to our members below and reach out to one of the group leads directly.

Last updated Jun 22 '17

Research Areas

Graphics & Vision

Group

Vision Group

Members