Face Reenactment
24 papers with code • 0 benchmarks • 1 datasets
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
Benchmarks
These leaderboards are used to track progress in Face Reenactment
AnimeCeleb
Latest papers
One-shot Face Reenactment
bj80heyue/Learning_One_Shot_Face_Reenactment
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However, in real-world scenario end-users often only have one target face at hand, rendering existing methods inapplicable.
FReeNet: Multi-Identity Face Reenactment
zhangzjn/FReeNet
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CVPR 2020
This paper presents a novel multi-identity face reenactment framework, named FReeNet, to transfer facial expressions from an arbitrary source face to a target face with a shared model.
ICface: Interpretable and Controllable Face Reenactment Using GANs
Blade6570/icface
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This paper presents a generic face animator that is able to control the pose and expressions of a given face image.
ReenactGAN: Learning to Reenact Faces via Boundary Transfer
A transformer is subsequently used to adapt the boundary of source face to the boundary of target face.
