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Found 8 papers, 3 papers with code
3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views
To close the gap between image domains, we create a large-scale dataset of diverse faces with gaze pseudo-annotations, which we extract based on the 3D geometry of the scene, and design a multi-view supervision framework to balance their effect during training.
Dynamic Neural Portraits
We present Dynamic Neural Portraits, a novel approach to the problem of full-head reenactment.
Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control
We present Free-HeadGAN, a person-generic neural talking head synthesis system.
Head2HeadFS: Video-based Head Reenactment with Few-shot Learning
Head reenactment is an even more challenging task, which aims at transferring not only the facial expression, but also the entire head pose from a source person to a target.
HeadGAN: One-shot Neural Head Synthesis and Editing
Recent attempts to solve the problem of head reenactment using a single reference image have shown promising results.
Head2Head++: Deep Facial Attributes Re-Targeting
Facial video re-targeting is a challenging problem aiming to modify the facial attributes of a target subject in a seamless manner by a driving monocular sequence.
ReenactNet: Real-time Full Head Reenactment
Video-to-video synthesis is a challenging problem aiming at learning a translation function between a sequence of semantic maps and a photo-realistic video depicting the characteristics of a driving video.
Head2Head: Video-based Neural Head Synthesis
In this paper, we propose a novel machine learning architecture for facial reenactment.
