A self-supervised domain adaptation technique enables high-fidelity face models to be driven from monocular commodity camera footage without target domain labels by leveraging consecutive frame texture consistency.
Self-supervised multi-level face model learning for monocular reconstruction at over 250 Hz
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Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking
A self-supervised domain adaptation technique enables high-fidelity face models to be driven from monocular commodity camera footage without target domain labels by leveraging consecutive frame texture consistency.