A Learned Radiance-Field Representation for Complex Luminaires release_rphx254pzvfc5duu7xvew4ssqi

by Jorge Condor, Adrián Jarabo

Released as a article .

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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Type  article
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Date   2022-07-11
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Language   en ?
arXiv  2207.05009v1
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