  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.
