论文标题
Supperol：反向渲染的超分辨率形状和反射率估计
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering
论文作者
论文摘要
我们提出了一个称为Supperol的端到端反向渲染管道，该管道使我们能够以超分辨率的方式从一组颜色图像中恢复3D形状和材料参数。为此，我们通过多层感知器表示双向反射分布函数（BRDF）和签名距离函数（SDF）。为了获得表面形状及其反射率特性，我们将其恢复为具有基于物理的照明模型的可区分体积渲染器，该模型使我们能够将反射率和照明解次。该物理模型考虑了相机点扩展功能的效果，从而使形状和材料以超分辨率的质量重建。实验验证证实，Supperol在反向渲染质量方面实现了最先进的性能。它生成的重建比单个输入图像更清晰，使该方法理想地适用于低分辨率图像的3D建模。
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.
