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 141–150 of 381 papers

TitleStatusHype
Generation of artificial facial drug abuse images using Deep De-identified anonymous Dataset augmentation through Genetics Algorithm (3DG-GA)—0
Dynamic Conditional Networks for Few-Shot Learning—0
Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning—0
Causal Adversarial Network for Learning Conditional and Interventional Distributions—0
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis—0
Cali-Sketch: Stroke Calibration and Completion for High-Quality Face Image Generation from Human-Like Sketches—0
DREAM-Talk: Diffusion-based Realistic Emotional Audio-driven Method for Single Image Talking Face Generation—0
DreamSalon: A Staged Diffusion Framework for Preserving Identity-Context in Editable Face Generation—0
BoostGAN for Occlusive Profile Face Frontalization and Recognition—0
Age-Oriented Face Synthesis with Conditional Discriminator Pool and Adversarial Triplet Loss—0
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