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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 11–20 of 68 papers

TitleStatusHype
Deepfake Generation and Detection: A Benchmark and SurveyCode4
AniPortrait: Audio-Driven Synthesis of Photorealistic Portrait AnimationCode9
DiffusionAct: Controllable Diffusion Autoencoder for One-shot Face Reenactment—0
One-shot Neural Face Reenactment via Finding Directions in GAN's Latent Space—0
Towards a Simultaneous and Granular Identity-Expression Control in Personalized Face Generation—0
Pose Adapted Shape Learning for Large-Pose Face ReenactmentCode1
FSRT: Facial Scene Representation Transformer for Face Reenactment from Factorized Appearance Head-pose and Facial Expression Features—0
EFHQ: Multi-purpose ExtremePose-Face-HQ dataset—0
Learning Dense Correspondence for NeRF-Based Face Reenactment—0
BakedAvatar: Baking Neural Fields for Real-Time Head Avatar SynthesisCode2
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