DarkGS: Learning Neural Illumination and 3D Gaussians Relighting for Robotic Exploration in the Dark

arXiv:2403.10814v1 Announce Type: new
Abstract: Humans have the remarkable ability to construct consistent mental models of an environment, even under limited or varying levels of illumination. We wish to endow robots with this same capability. In this paper, we tackle the challenge of constructing a photorealistic scene representation under poorly illuminated conditions and with a moving light source. We approach the task of modeling illumination as a learning problem, and utilize the developed illumination model to aid in scene reconstruction. …

abstract arxiv capability challenge consistent construct cs.cv cs.ro environment exploration humans paper photorealistic robotic robots type