We propose a novel Neural Radiance Field (NeRF) representation for non-opaque
scenes that allows fast inference by utilizing textured polygons. Despite the
high-quality novel view rendering that NeRF provides, a critical limitation is
that it relies on volume rendering that can be computationally expensive and
does not utilize the advancements in modern graphics hardware. Existing methods
for this problem fall short when it comes to modelling volumetric effects as
they rely purely on surface rendering. We thus propose to model the scene with
polygons, which can then be used to obtain the quadrature points required to
model volumetric effects, and also their opacity and colour from the texture.
To obtain such polygonal mesh, we train a specialized field whose
zero-crossings would correspond to the quadrature points when volume rendering,
and perform marching cubes on this field. We then rasterize the polygons and
utilize the fragment shaders to obtain the final colour image. Our method
allows rendering on various devices and easy integration with existing graphics
frameworks while keeping the benefits of volume rendering alive.

我们提出了一种新颖的神经辐射场（NeRF）表示，用于非不透明场景，通过利用带纹理的多边形实现快速推理。我们的方法通过对场景进行多边形建模，从纹理中获取不透明度和颜色，并使用透像渲染所需的象限点来模拟体积效应，从而克服了现有方法在体积渲染和建模体积效应方面的局限性。最终色彩图像通过光栅化多边形和片段着色器得到，我们的方法能够在各种设备上进行渲染，并与现有图形框架轻松集成，同时保持体积渲染的优势。

基于预计算四元数场的体密度渲染

Volumetric Rendering with Baked Quadrature Fields

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.

本文介绍了一种基于纹理多边形的新型 NeRF 表示方法，能够高效地使用标准渲染管道合成新图像，这种方法允许使用传统的多边形光栅化方法对 NeRF 进行渲染，从而在各种计算平台上实现交互式帧速率。