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（NeRFs）在从新视角合成三维场景图像方面展现出惊人能力。然而，它们依赖于基于光线步进的专业化体渲染算法，这与广泛部署的图形硬件的能力不匹配。本文提出一种基于纹理化多边形的新型NeRF表示方法，该方法可利用标准渲染管线高效合成新视角图像。该NeRF表示为一系列多边形，其纹理包含二值不透明度和特征向量。通过Z缓存对这些多边形进行传统渲染，可在每个像素处生成特征图像，随后由运行在片段着色器中的小型视角相关MLP进行解释，以生成最终像素颜色。该方法使NeRF能够通过传统多边形光栅化管线进行渲染，从而获得海量像素级并行性，在包括移动电话在内的广泛计算平台上实现交互式帧率。