SOTAVerified

Face Generation

Face generation is the task of generating (or interpolating) new faces from an existing dataset.

The state-of-the-art results for this task are located in the Image Generation parent.

( Image credit: Progressive Growing of GANs for Improved Quality, Stability, and Variation )

Papers

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Showing 151–160 of 381 papers

TitleStatusHype
Generation of artificial facial drug abuse images using Deep De-identified anonymous Dataset augmentation through Genetics Algorithm (3DG-GA)—0
Domain Private and Agnostic Feature for Modality Adaptive Face Recognition—0
DisentTalk: Cross-lingual Talking Face Generation via Semantic Disentangled Diffusion Model—0
BENet: A Cross-domain Robust Network for Detecting Face Forgeries via Bias Expansion and Latent-space Attention—0
Disentangled Lifespan Face Synthesis—0
DiffUMI: Training-Free Universal Model Inversion via Unconditional Diffusion for Face Recognition—0
BareSkinNet: De-makeup and De-lighting via 3D Face Reconstruction—0
Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation—0
DiffTalker: Co-driven audio-image diffusion for talking faces via intermediate landmarks—0
AVI-Talking: Learning Audio-Visual Instructions for Expressive 3D Talking Face Generation—0
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