Impressive eye motion capture and reconstruction for Facebook’s avatars.

Interacting with people across large distances is important for remote work, interpersonal relationships, and entertainment. While such face-to-face interactions can be achieved using 2D video conferencing or, more recently, virtual reality (VR), telepresence systems currently distort the communication of eye contact and social gaze signals. Although methods have been proposed to redirect gaze in 2D teleconferencing situations to enable eye contact, 2D video conferencing lacks the 3D immersion of real life. To address these problems, we develop a system for face-to-face interaction in VR that focuses on reproducing photorealistic gaze and eye contact. To do this, we create a 3D virtual avatar model that can be animated by cameras mounted on a VR headset to accurately track and reproduce human gaze in VR. Our primary contributions in this work are a jointly-learnable 3D face and eyeball model that better represents gaze direction and upper facial expressions, a method for disentangling the gaze of the left and right eyes from each other and the rest of the face allowing the model to represent entirely unseen combinations of gaze and expression, and a gaze-aware model for precise animation from headset-mounted cameras. Our quantitative experiments show that our method results in higher reconstruction quality, and qualitative results show our method gives a greatly improved sense of presence for VR avatars.

Read the paper here.