基于单图重建人体3D模型，同时精准捕捉面部形态与外观特征。
SARS: A Novel Face and Body Shape and Appearance Aware 3D Reconstruction System extends Morphable Models
- 提出模块化系统SARS，从单张图像中联合提取人脸与身体信息
- 融合年龄、性别等高阶语义特征，提升3D重建的细节真实度
- 适合需要精细人体建模的数字人、影视特效等应用
3DMM是一种以2D图像为输入、重建3D物体结构与外观的可变形模型，尤其适用于人脸和人体。3DMM通过结合身份与表情混合形状及基础网格生成详细3D模型，其变化可通过调节多种参数控制，如形状、纹理、光照和相机参数等。以往研究主要关注全局面部结构或几何，忽略了年龄、性别、面部关键点等高阶语义特征，这些特征刻画了面部边界、曲线、凹陷与皱纹。为此，本文提出一种形状与外观感知的3D重建系统SARS，采用模块化流程，从单张图像中提取面部与身体信息，实现对人体完整3D模型的精确重建。
原文摘要 · Abstract (English)
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.
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