Back to results

York University

AI-Assisted Pipeline for 3D Face Avatar Generation

Abstract

dc:description.abstract

Filling virtual environments with realistic-looking avatars is essential for games, film production, and virtual reality. Creating a fun and engaging experience requires a wide variety of different-looking avatars. There are two main methods to create realistic-looking avatars. One is to scan a real person's face using a light room. The second is for the artist/designer to create the avatar manually using advanced tools. Both of these approaches are expensive in terms of time, computing, and human labour. This thesis leverages generative models like Generative Adversarial Networks (GANs) and Variational Auto-Encoders (VAEs) to automate avatar creation. Our pipeline offers control over three aspects: face shape, skin color, and fine details like beards or wrinkles. This provides artists flexibility in avatar creation and can integrate with tools like MOSAR for controlling avatars from 2D images.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Fadaeinejad, Amin
Advisor dc:contributor.advisor
  • Troje, Nikolaus

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10315/42489
OAI identifier oai:identifier
oai:yorkspace.library.yorku.ca:10315/42489

Chain of custody

source
Harvested from
York University
Base URL
yorkspace.library.yorku.ca/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Fadaeinejad, Amin. AI-Assisted Pipeline for 3D Face Avatar Generation. 2024. https://hdl.handle.net/10315/42489