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
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该研究提出了一种新的基于低成本公开数据的三维可塑面反射模型，使用线性光泽加权来表示具有空间变化的高光强度和光泽数值的参数建模，然后开发了一种逆渲染算法来重建反射参数，进而训练了一个初步的可塑性反射模型，再通过 “重建更新” 策略对自然环境中的数据集进行了微调，实验证明该方法可以获得逼真的面部高光效果