3D Morphable Models are a class of generative models commonly used to model faces. They are typically applied to ill-posed problems such as 3D reconstruction from 2D data. Several ambiguities in this problem's image formation process have been studied explicitly. We demonstrate that non-orthogonality of the variation in identity and expression can cause identity-expression ambiguity in 3D Morphable Models, and that in practice expression and identity are far from orthogonal and can explain each other surprisingly well. Whilst previously reported ambiguities only arise in an inverse rendering setting, identity-expression ambiguity emerges in the 3D shape generation process itself. We demonstrate this effect with 3D shapes directly as well as through an inverse rendering task, and use two popular models built from high quality 3D scans as well as a model built from a large collection of 2D images and videos. We explore this issue's implications for inverse rendering and observe that it cannot be resolved by a purely statistical prior on identity and expression deformations.
翻译:3D 负式模型是常用于模拟面部的基因模型。 它们通常适用于错误的问题, 例如 2D 数据重建 3D 。 这个问题的图像形成过程已经明确研究过若干模糊之处。 我们证明, 身份和表达方式差异的不辨别性可能会在 3D 负式模型中造成身份表达的模糊性, 实际上, 表达方式和身份远非正方形, 并且可以令人惊讶地解释对方 。 虽然以前报告的模糊性只出现在反向翻版设置中, 身份表达的模糊性在 3D 形状生成过程本身中出现 。 我们直接和通过反向翻版任务展示了 3D 形状的这种效果, 并使用由高质量 3D 扫描制成的两种流行模型以及从大量收集 2D 图像和视频中建成的模型。 我们探讨这个问题对反向演化的影响, 并且指出, 这个问题不可能通过纯粹的统计先验身份和表达变形来加以解决 。