Paper

Ultraman: Single Image 3D Human Reconstruction with Ultra Speed and Detail

Chen, Xiaoxue, Ye, Xiaojun, Huan-ang Gao, Chen, Mingjin, Chen, Junhao, Fan, Zhaoxin, Zhao, Hao

2024

Overview

3D human body reconstruction has been a challenge in the field of computer vision. Previous methods are often time-consuming and difficult to capture the detailed appearance of the human body. In this paper, we propose a new method called \\emph{Ultraman} for fast reconstruction of textured 3D human models from a single image. Compared to existing techniques, \\emph{Ultraman} greatly improves the reconstruction speed and accuracy while preserving high-quality texture details. We present a set of new frameworks for human reconstruction consisting of three parts, geometric reconstruction, texture generation and texture mapping. Firstly, a mesh reconstruction framework is used, which accurately extracts 3D human shapes from a single image. At the same time, we propose a method to generate a multi-view consistent image of the human body based on a single image. This is finally combined with a novel texture mapping method to optimize texture details and ensure color consistency during reconstruction. Through extensive experiments and evaluations, we demonstrate the superior performance of \\emph{Ultraman} on various standard datasets. In addition, \\emph{Ultraman} outperforms state-of-the-art methods in terms of human rendering quality and speed. Upon acceptance of the article, we will make the code and data publicly available.

• Publisher: Cornell University Library, arXiv.org
• Subject: Computer vision / Finite element method / Human body / Image reconstruction / Texture mapping / Three dimensional models