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

TL;DR

Ultraman is a novel method for rapid, detailed 3D human reconstruction from a single image, significantly improving speed and accuracy while maintaining high-quality textures.

Contribution

It introduces a comprehensive framework combining geometric reconstruction, multi-view consistent image generation, and advanced texture mapping for single-image 3D human modeling.

Findings

Outperforms existing methods in speed and accuracy

Produces high-quality textured 3D human models

Demonstrates superior performance on standard datasets

Abstract

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.