A Learned Radiance-Field Representation for Complex Luminaires
Informazioni aggiuntive
Autori
Curatori
Condor Lacambra J.,
Jarabo A.
Tipo
Atti di conferenza
Anno
2022
Lingua
Inglese
Abstract
We propose an efficient method for rendering complex luminaires using a high'quality octree-based representation of the luminaire emission. Complex luminaires are a particularly challenging problem in rendering, due to their caustic light paths inside the luminaire. We reduce the geometric complexity of luminaires by using a simple proxy geometry and encode the visually-complex emitted light field by using a neural radiance field. We tackle the multiple challenges of using NeRFs for representing luminaires, including their high dynamic range, high-frequency content and null-emission areas, by proposing a specialized loss function. For rendering, we distill our luminaires' NeRF into a plenoctree, which we can be easily integrated into traditional rendering systems. Our approach allows for speed-ups of up to 2 orders of magnitude in scenes containing complex luminaires introducing minimal error.
Mese
luglio
Editore
The Eurographics Association
Nome conferenza
EGSR 2022
ISBN
9783038681878
ISSN
1727-3463
Curatore
Ghosh, Abhijeet and Wei, Li-Yi
