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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 61–68 of 68 papers

TitleStatusHype
KoDF: A Large-scale Korean DeepFake Detection Dataset—0
Learning Dense Correspondence for NeRF-Based Face Reenactment—0
Learning Identity-Invariant Motion Representations for Cross-ID Face Reenactment—0
Learning Online Scale Transformation for Talking Head Video Generation—0
LI-Net: Large-Pose Identity-Preserving Face Reenactment Network—0
MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targets—0
MaskRenderer: 3D-Infused Multi-Mask Realistic Face Reenactment—0
Mesh Guided One-shot Face Reenactment using Graph Convolutional Networks—0
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