BriefGPT.xyz
Dec, 2017
自监督多层面部模型学习,在超过250 Hz的单目重建中
Self-supervised Multi-level Face Model Learning for Monocular Reconstruction at over 250 Hz
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Ayush Tewari, Michael Zollhöfer, Pablo Garrido, Florian Bernard, Hyeongwoo Kim...
TL;DR
本论文提出了一种基于联合学习参数人脸模型和面部形状、表情、反射和照明的回归器的方法,其结合了3D可塑模型(3D Morphable Model)的优点和学习校正空间的空外推广优点。
Abstract
The reconstruction of dense
3d
models of
face geometry
and appearance from a single image is highly challenging and ill-posed. To constrain the problem, many approaches rely on strong priors, such as parametric f
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