基于注意网络的复杂物体材料反射率估计

Bin Cheng, Junli Zhao, Fuqing Duan
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引用次数: 0

摘要

材料反射率属性建模可以用于逼真渲染,为虚拟物体生成逼真的外观。然而,目前的工作主要集中在近平面物体上。在本文中,我们提出了一个端到端的网络框架,该框架具有注意机制,可以从单幅图像中估计任意3D物体表面的反射特性,其中每个反射特性分别使用单个注意模块来学习属性的特定特征。我们还通过渲染一组3D复杂形状模型来生成材料数据集。该数据集适用于任意形状复杂物体的反射率估计。实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Material Reflectance Property Estimation of Complex Objects Using an Attention Network
Material reflectance property modeling can be used in realistic ren-dering to generate realistic appearances for virtual objects. However, current works mainly focus on near plane objects. In this paper, we propose an end-to-end network framework with attention mecha-nism to estimate the reflectance properties of any 3D object surface from a single image, where a single attention module is used for each reflectance property respectively to learn the property specific features. We also generate a material dataset by rendering a set of 3D complex shape models. The dataset is suitable for reflectance property estimation of arbitrary complex shape objects. Experiments validate the proposed method.
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