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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 51–68 of 68 papers

TitleStatusHype
FSRT: Facial Scene Representation Transformer for Face Reenactment from Factorized Appearance, Head-pose, and Facial Expression Features—0
FSRT: Facial Scene Representation Transformer for Face Reenactment from Factorized Appearance Head-pose and Facial Expression Features—0
G3FA: Geometry-guided GAN for Face Animation—0
High-fidelity Facial Avatar Reconstruction from Monocular Video with Generative Priors—0
KoDF: A Large-scale Korean DeepFake Detection Dataset—0
Learning Dense Correspondence for NeRF-Based Face Reenactment—0
Single Source One Shot Reenactment using Weighted motion From Paired Feature Points—0
Thinking the Fusion Strategy of Multi-reference Face Reenactment—0
ToonTalker: Cross-Domain Face Reenactment—0
Towards a Simultaneous and Granular Identity-Expression Control in Personalized Face Generation—0
UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing—0
Reenact Anything: Semantic Video Motion Transfer Using Motion-Textual Inversion—0
ReenactGAN: Learning to Reenact Faces via Boundary TransferCode0
FReeNet: Multi-Identity Face ReenactmentCode0
One-shot Face ReenactmentCode0
MagicPortrait: Temporally Consistent Face Reenactment with 3D Geometric GuidanceCode0
ICface: Interpretable and Controllable Face Reenactment Using GANsCode0
FSGAN: Subject Agnostic Face Swapping and ReenactmentCode0
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