We propose an analysis-by-synthesis method for fast multi-view 3D reconstruction of opaque objects with arbitrary materials and illumination. State-of-the-art methods use both neural surface representations and neural rendering. While flexible, neural surface representations are a significant bottleneck in optimization runtime. Instead, we represent surfaces as triangle meshes and build a differentiable rendering pipeline around triangle rasterization and neural shading. The renderer is used in a gradient descent optimization where both a triangle mesh and a neural shader are jointly optimized to reproduce the multi-view images. We evaluate our method on a public 3D reconstruction dataset and show that it can match the reconstruction accuracy of traditional baselines and neural approaches while surpassing them in optimization runtime. Additionally, we investigate the shader and find that it learns an interpretable representation of appearance, enabling applications such as 3D material editing.

提出了一种分析合成方法，用于快速多视角不透明物体的三维重建，通过将表面表示为三角形网格并围绕三角形光栅化和神经阴影构建可微分的渲染管道，优化三角形网格和神经着色器来重现多视图图像，并研究了着色器，发现它学习了可解释的外观表示。

神经延迟着色的多视角网格重建