Abstract
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.
Abstract (translated)
可变形模型（3DMM）是一种将2D图像作为输入，重建三维物体的结构和外观的形态模型，特别是在人类面部和身体方面。3DMM通过结合身份和表情变化形状与基本面部网格来创建详细的三维模型。可以通过调整多样化的参数来控制3D可变形模型中的变异，这些参数包括高层次的图像描述符，如形状、纹理、光照以及相机参数。以往关于3D人体重建的研究主要集中在全局面部结构或几何形状上，而忽略了年龄、性别等定义面部边界的特征、曲线、凹陷和皱纹这样的面部语义特征。为了适应这些高层次的人脸特征的变化，本工作引入了一种基于感知形状与外观的三维重构系统（我们命名为SARS），这是一个模块化流程，可以从单张图像中提取身体和面部信息以准确重建完整人体的3D模型。
URL
https://arxiv.org/abs/2602.09918
