Use the GDC 2021 Session Viewer to browse and sort the ever-growing list of sessions by pass type, topic, and format. You will be able to build your personal schedule directly within the event platform, once live early July 2021.
Pei Li (Senior AI Researcher, Netease Games AILAB)
Pass Type: All Access Pass, Summits Pass
Vault Recording: TBD
Audience Level: N/A: I prefer to present live on-site but I am open to delivering a virtual presentation
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.
Attendees will learn what is a 3D parametric face model, how to build a 3D parametric face model, and how to utilize this model for 3D facial content-creation and in-game applications.
This presentation is intended for researchers and developers working on "faces", who want to learn how a parametric face model can be practically used in games, and artists who want to learn how their production efficiency can be potentially improved by this technique.