Democratizing the Creation of Animatable Facial Avatars
Yilin Zhu, Dalton Omens, Haodi He, Ron Fedkiw

TL;DR
This paper introduces a democratized pipeline for creating personalized animatable facial avatars without high-end hardware, using image warping and projection techniques to reconstruct geometry and texture from real-world images.
Contribution
A novel method that leverages image warping and projection to build personalized facial avatars without expensive equipment, enabling easier and more accessible avatar creation.
Findings
Effective reconstruction of geometry for multiple expressions
Ability to create personalized animation rigs
Improved avatar quality post-import
Abstract
In high-end visual effects pipelines, a customized (and expensive) light stage system is (typically) used to scan an actor in order to acquire both geometry and texture for various expressions. Aiming towards democratization, we propose a novel pipeline for obtaining geometry and texture as well as enough expression information to build a customized person-specific animation rig without using a light stage or any other high-end hardware (or manual cleanup). A key novel idea consists of warping real-world images to align with the geometry of a template avatar and subsequently projecting the warped image into the template avatar's texture; importantly, this allows us to leverage baked-in real-world lighting/texture information in order to create surrogate facial features (and bridge the domain gap) for the sake of geometry reconstruction. Not only can our method be used to obtain a…
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Taxonomy
TopicsFashion and Cultural Textiles
MethodsALIGN
