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FaceVR: Real-Time Facial Reenactment and Eye Gaze Control in Virtual Reality

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arxiv 1610.03151 v2 pith:LM3JC2V7 submitted 2016-10-11 cs.CV

classification cs.CV
keywords facevrfacialtrackingvideoenablesfacegazeimage-based
verification ladder T0 review T1 audit T2 compute T3 formal
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We propose FaceVR, a novel image-based method that enables video teleconferencing in VR based on self-reenactment. State-of-the-art face tracking methods in the VR context are focused on the animation of rigged 3d avatars. While they achieve good tracking performance the results look cartoonish and not real. In contrast to these model-based approaches, FaceVR enables VR teleconferencing using an image-based technique that results in nearly photo-realistic outputs. The key component of FaceVR is a robust algorithm to perform real-time facial motion capture of an actor who is wearing a head-mounted display (HMD), as well as a new data-driven approach for eye tracking from monocular videos. Based on reenactment of a prerecorded stereo video of the person without the HMD, FaceVR incorporates photo-realistic re-rendering in real time, thus allowing artificial modifications of face and eye appearances. For instance, we can alter facial expressions or change gaze directions in the prerecorded target video. In a live setup, we apply these newly-introduced algorithmic components.

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  1. Discovering Geometric Biases in 3D Face Reconstruction: A Curvature-Aware Spectral Framework for Fairness Evaluation

    cs.CV 2026-07 conditional novelty 6.0 of 10

    A curvature-aware spectral framework using the Laplace-Beltrami operator detects demographic biases in 3D face reconstruction that Euclidean metrics miss, validated by a user study showing 73.6% perceptual accuracy.

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