We propose an end-to-end inverse rendering pipeline called SupeRVol that allows us to recover 3D shape and material parameters from a set of color images in a super-resolution manner. To this end, we represent both the bidirectional reflectance distribution function (BRDF) and the signed distance function (SDF) by multi-layer perceptrons. In order to obtain both the surface shape and its reflectance properties, we revert to a differentiable volume renderer with a physically based illumination model that allows us to decouple reflectance and lighting. This physical model takes into account the effect of the camera's point spread function thereby enabling a reconstruction of shape and material in a super-resolution quality. Experimental validation confirms that SupeRVol achieves state of the art performance in terms of inverse rendering quality. It generates reconstructions that are sharper than the individual input images, making this method ideally suited for 3D modeling from low-resolution imagery.

翻译：我们提出了一种名为SupeRVol的端到端逆渲染流水线，能够从一组彩色图像中以超分辨率方式恢复三维形状与材质参数。为此，我们采用多层感知机分别表示双向反射分布函数（BRDF）和符号距离函数（SDF）。为同时获取表面形状及其反射属性，我们借助基于物理光照模型的可微分体渲染器，该模型允许我们解耦反射率与光照。该物理模型考虑了相机点扩散函数的影响，从而能够以超分辨率质量重建形状与材质。实验验证表明，SupeRVol在逆渲染质量方面达到了当前最优性能。其生成的重建结果比原始输入图像更清晰，使该方法特别适用于从低分辨率图像进行三维建模。