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Neural Radiance Fields (NeRFs) have demonstrated amazing ability tosynthesize images of 3D scenes from novel views. However, they rely uponspecialized volumetric rendering algorithms based on ray marching that aremismatched to the capabilities of widely deployed graphics hardware. This paperintroduces a new NeRF representation based on textured polygons that cansynthesize novel images efficiently with standard rendering pipelines. The NeRFis represented as a set of polygons with textures representing binary opacitiesand feature vectors. Traditional rendering of the polygons with a z-bufferyields an image with features at every pixel, which are interpreted by a small,view-dependent MLP running in a fragment shader to produce a final pixel color.This approach enables NeRFs to be rendered with the traditional polygonrasterization pipeline, which provides massive pixel-level parallelism,achieving interactive frame rates on a wide range of compute platforms,including mobile phones.

MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures