A Learned Radiance-Field Representation for Complex Luminaires

• URL: http://arxiv.org/abs/2207.05009v1
• Date: Mon, 11 Jul 2022 16:57:59 GMT
• Title: A Learned Radiance-Field Representation for Complex Luminaires
• Abstract summary: We reduce the geometric complexity of luminaires by using a simple proxy geometry. We encode the visually-complex emitted light field by using a neural radiance field. For rendering, we distill our luminaires' NeRF into a Plenoctree, which we can be easily integrated into traditional rendering systems.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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