You've been logged out of GDC Vault since the maximum users allowed for this account has been reached. To access Members Only content on GDC Vault, please log out of GDC Vault from the computer which last accessed this account.

Click here to find out about GDC Vault Membership options for more users.

close

The Number One Educational Resource for the Game Industry

Session Name: Machine Learning Summit: 3D Parametric Face Model and Its Applications in Games
Speaker(s): Pei Li
Company Name(s): Netease Games AILAB
Track / Format: Machine Learning Summit

Did you know free users get access to 30% of content from the last 2 years?


Get your team full access to the most up to date GDC content

Overview: There always exist a huge demand for high-quality 3D facial assets in the game industry, but producing 3D facial assets is a costly and time-consuming task. Fortunately, some recent research progress on 3D Morphable Face Models (3DMM) can be utilized to facilitate this process (i.e., modeling, rigging and animation). In NetEase Games, we built a custom 3D parametric face model, around which, we developed a series of techniques for 3D facial content-creation and in-game applications. This session will introduce what is and how to build such a 3D parametric face model, and give implementation details to three techniques built upon this model, i.e., creating face meshes from images, producing shape and expression variations from one example face mesh, and facial performance capture.

Game Developers Conference 2021

Pei Li

Netease Games AILAB

free content

Machine Learning Summit

Programming