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Face Reenactment

Face Reenactment is an emerging conditional face synthesis task that aims at fulfilling two goals simultaneously: 1) transfer a source face shape to a target face; while 2) preserve the appearance and the identity of the target face.

Source: One-shot Face Reenactment

Papers

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Showing 21–30 of 68 papers

TitleStatusHype
MaskRenderer: 3D-Infused Multi-Mask Realistic Face Reenactment—0
ToonTalker: Cross-Domain Face Reenactment—0
HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget FacesCode1
On the Vulnerability of DeepFake Detectors to Attacks Generated by Denoising Diffusion Models—0
ReliableSwap: Boosting General Face Swapping Via Reliable SupervisionCode2
StyleAvatar: Real-time Photo-realistic Portrait Avatar from a Single VideoCode2
Unsupervised Facial Performance Editing via Vector-Quantized StyleGAN Representations—0
High-fidelity Facial Avatar Reconstruction from Monocular Video with Generative Priors—0
Compressing Video Calls using Synthetic Talking Heads—0
Audio-Visual Face ReenactmentCode1
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