  Precomputed Radiance Transfer (PRT) is widely used for real-time
photorealistic effects. PRT disentangles the rendering equation into transfer
and lighting, enabling their precomputation. Transfer accounts for the
cosine-weighted visibility of points in the scene while lighting for emitted
radiance from the environment. Prior art stored precomputed transfer in a
tabulated manner, either in vertex or texture space. These values are fetched
with interpolation at each point for shading. Vertex space methods require
densely tessellated mesh vertices for high quality images. Texture space
methods require non-overlapping and area-preserving UV mapping to be available.
They also require a high-resolution texture to avoid rendering artifacts. In
this paper, we propose a compact transfer representation that is learnt
directly on scene geometry points. Specifically, we train a small multi-layer
perceptron (MLP) to predict the transfer at sampled surface points. Our
approach is most beneficial where inherent mesh storage structure and natural
UV mapping are not available, such as Implicit Surfaces as it learns the
transfer values directly on the surface. We demonstrate real-time,
photorealistic renderings of diffuse and glossy materials on SDF geometries
with PRT using our approach.
