A Learned Radiance-Field Representation for Complex Luminaires
release_rphx254pzvfc5duu7xvew4ssqi
by
Jorge Condor, Adrián Jarabo
2022
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.
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