Human avatars synthesis technologies: a survey

Abstract

Nowadays, the demand for efficient human avatars modeling is becoming increasingly urgent since metaverse has attracted more and more attention.Creating human avatars from human image datasets has always been a popular topic in the field of computer vision.3D human avatars synthesis can be regarded as a sub-module of 3D reconstruction focusing on reproducing the complex articulated body and surface details of human.A comprehensive survey of the literature related to the human reconstruction in recent years was conducted, including the work of full-body avatars, talking-head and clothing modeling.By analyzing and summarizing existing work, human avatars synthesis technologies were divided into five categories: mesh-based methods, image-based methods, voxel-based methods, implicit methods and hybrid methods due to the features of their pipelines.Firstly, the basic principles of them were introduced respectively.Secondly, the realization based on related work was discussed and then the advantages and disadvantages of methods respectively were pointed out.Thirdly, the datasets and metrics for model quality evaluation were introduced.Besides, an overview of various applications was given.Finally, the future directions of human avatars synthesis technology were prospected to synthesize high-quality, high-fidelity and low-latency human avatars.

Keywords

• metaverse;human avatars;three-dimensional human reconstruction;computer vision;deep learning;face synthesis