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 201–210 of 381 papers

TitleStatusHype
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder—0
Data Synthesis with Diverse Styles for Face Recognition via 3DMM-Guided Diffusion—0
DeepFace: Face Generation using Deep Learning—0
Dense-Face: Personalized Face Generation Model via Dense Annotation Prediction—0
Detecting Face Synthesis Using a Concealed Fusion Model—0
Differential Generative Adversarial Networks: Synthesizing Non-linear Facial Variations with Limited Number of Training Data—0
DiffTalker: Co-driven audio-image diffusion for talking faces via intermediate landmarks—0
Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation—0
DiffUMI: Training-Free Universal Model Inversion via Unconditional Diffusion for Face Recognition—0
Disentangled Lifespan Face Synthesis—0
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