Neural Radiance Fields (NeRFs) have demonstrated amazing ability to synthesize images of 3D scenes from novel views. However, they rely upon specialized volumetric rendering algorithms based on ray marching that are mismatched to the capabilities of widely deployed graphics hardware. This paper introduces a new NeRF representation based on textured polygons that can synthesize novel images efficiently with standard rendering pipelines. The NeRF is represented as a set of polygons with textures representing binary opacities and feature vectors. Traditional rendering of the polygons with a z-buffer yields 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 polygon rasterization pipeline, which provides massive pixel-level parallelism, achieving interactive frame rates on a wide range of compute platforms, including mobile phones.

翻译：神经辐射场（NeRF）在从新视角合成三维场景图像方面展现了惊人的能力。然而，它们依赖于基于光线步进的专业化体积渲染算法，这与广泛部署的图形硬件能力不匹配。本文提出一种基于纹理多边形的新型NeRF表示方法，该方法可通过标准渲染流水线高效合成新视角图像。该NeRF由一组带有二进制不透明度和特征向量纹理的多边形表示。通过使用z-buffer的传统多边形渲染，每个像素处生成带有特征的图像，这些特征由运行在片段着色器中的小型视点相关MLP解释，以产生最终像素颜色。该方法使得NeRF能够通过传统多边形光栅化流水线进行渲染，该流水线提供海量像素级并行性，从而在包括移动电话在内的多种计算平台上实现交互式帧率。