Modeling non-Lambertian effects such as facial specularity leads to a more realistic 3D Morphable Face Model. Existing works build parametric models for diffuse and specular albedo using Light Stage data. However, only diffuse and specular albedo cannot determine the full BRDF. In addition, the requirement of Light Stage data is hard to fulfill for the research communities. This paper proposes the first 3D morphable face reflectance model with spatially varying BRDF using only low-cost publicly-available data. We apply linear shiness weighting into parametric modeling to represent spatially varying specular intensity and shiness. Then an inverse rendering algorithm is developed to reconstruct the reflectance parameters from non-Light Stage data, which are used to train an initial morphable reflectance model. To enhance the model's generalization capability and expressive power, we further propose an update-by-reconstruction strategy to finetune it on an in-the-wild dataset. Experimental results show that our method obtains decent rendering results with plausible facial specularities. Our code is released \href{https://yxuhan.github.io/ReflectanceMM/index.html}{\textcolor{magenta}{here}}.

翻译：建模非朗伯效应（如面部镜面反射）能够生成更逼真的三维可变形人脸模型。现有方法利用Light Stage数据构建漫反射和镜面反照率的参数模型，然而仅凭漫反射和镜面反照率无法完整描述双向反射分布函数（BRDF），且Light Stage数据的获取需求对研究社区难以满足。本文首次提出仅使用低成本公开数据，构建具有空间变化BRDF的三维可变形人脸反射模型。我们将线性光泽度权重引入参数建模，以表征空间变化的镜面强度和光泽度。进一步开发逆渲染算法，从非Light Stage数据中重建反射参数，用于训练初始的可变形反射模型。为增强模型的泛化能力和表达力，我们提出"重建-更新"策略，在野外数据集上对模型进行微调。实验结果表明，该方法能生成具有合理面部镜面反射效果的高质量渲染结果。我们的代码已开源：\href{https://yxuhan.github.io/ReflectanceMM/index.html}{\textcolor{magenta}{\texttt{此处}}}。