Morphable Models (3DMMs) are a type of morphable model that takes 2D images as inputs and recreates the structure and physical appearance of 3D objects, especially human faces and bodies. 3DMM combines identity and expression blendshapes with a basic face mesh to create a detailed 3D model. The variability in the 3D Morphable models can be controlled by tuning diverse parameters. They are high-level image descriptors, such as shape, texture, illumination, and camera parameters. Previous research in 3D human reconstruction concentrated solely on global face structure or geometry, ignoring face semantic features such as age, gender, and facial landmarks characterizing facial boundaries, curves, dips, and wrinkles. In order to accommodate changes in these high-level facial characteristics, this work introduces a shape and appearance-aware 3D reconstruction system (named SARS by us), a c modular pipeline that extracts body and face information from a single image to properly rebuild the 3D model of the human full body.

翻译：可变形模型（3DMMs）是一类以二维图像为输入、重建三维物体（特别是人脸和人体）结构与物理外观的可变形模型。3DMM将身份与表情混合形状与基础面部网格相结合，以生成精细的三维模型。三维可变形模型的变异性可通过调整多种参数进行控制，这些参数是高层级的图像描述符，例如形状、纹理、光照和相机参数。以往的三维人体重建研究仅关注全局面部结构或几何特征，忽略了年龄、性别以及表征面部边界、曲线、凹陷与皱纹的面部标志点等语义特征。为适应这些高层级面部特征的变化，本研究提出了一种形状与外观感知的三维重建系统（我们将其命名为SARS），该系统采用模块化流程，从单张图像中提取身体与面部信息，以准确重建人体全身的三维模型。