Ultraman: Single Image 3D Human Reconstruction with Ultra Speed and Detail
<|reference_start|>Ultraman: Single Image 3D Human Reconstruction with Ultra Speed and Detail: 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.<|reference_end|>
@article{chen2024ultraman:,
    title={Ultraman: Single Image 3D Human Reconstruction with Ultra Speed and
  Detail},
    author={Mingjin Chen, Junhao Chen, Xiaojun Ye, Huan-ang Gao, Xiaoxue Chen,
  Zhaoxin Fan, Hao Zhao},
    journal={arXiv preprint arXiv:2403.12028},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.12028},
    primaryClass={cs.CV cs.AI eess.IV}
}