HTML: A Parametric Hand Texture Model for 3D Hand Reconstruction and Personalization
HTML: A Parametric Hand Texture Model for 3D Hand Reconstruction and Personalization
复制标题
HTML：用于 3D 手部重建和个性化的参数化手部纹理模型
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
C. Theobalt
中科院分区：
文献类型：
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作者：
Neng Qian;Jiayi Wang;Franziska Mueller;Florian Bernard;Vladislav Golyanik;C. Theobalt
从图像中重建三维手是计算机视觉和图形学中一个被广泛研究的问题，与虚拟和增强现实具有特别高的相关性。虽然一些3D手重建方法利用手模型作为一个强大的之前解决歧义和实现更稳健的结果，大多数现有的模型只考虑手的形状和姿势，不模拟纹理。为了填补这一空白，在这项工作中，我们提出了HTML，第一个参数化人手纹理模型。我们的模型跨越了手部外观变化的几个维度（例如，与性别、种族或年龄相关），并且只需要一个商用相机来获取数据。通过实验，我们证明了我们的外观模型可以用于解决一系列具有挑战性的问题，例如从单个单眼图像中重建3D手部。此外，我们的外观模型可以用来定义一个神经渲染层，使训练具有自监督光度损失。我们让我们的模型公开可用。
3D hand reconstruction from images is a widely-studied problem in computer vision and graphics, and has a particularly high relevance for virtual and augmented reality. Although several 3D hand reconstruction approaches leverage hand models as a strong prior to resolve ambiguities and achieve more robust results, most existing models account only for the hand shape and poses and do not model the texture. To fill this gap, in this work we present HTML, the first parametric texture model of human hands. Our model spans several dimensions of hand appearance variability (e.g., related to gender, ethnicity, or age) and only requires a commodity camera for data acquisition. Experimentally, we demonstrate that our appearance model can be used to tackle a range of challenging problems such as 3D hand reconstruction from a single monocular image. Furthermore, our appearance model can be used to define a neural rendering layer that enables training with a selfsupervised photometric loss. We make our model publicly available.
DOI：
10.1109/iccv.2017.401
发表时间：
2017-03
期刊：
2017 IEEE International Conference on Computer Vision (ICCV)
影响因子：
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作者：
A. Tewari;M. Zollhöfer;Hyeongwoo Kim;Pablo Garrido;Florian Bernard;P. Pérez;C. Theobalt
通讯作者：
A. Tewari;M. Zollhöfer;Hyeongwoo Kim;Pablo Garrido;Florian Bernard;P. Pérez;C. Theobalt