ChildDiffusion: Unlocking the Potential of Generative AI and Controllable Augmentations for Child Facial Data Using Stable Diffusion and Large Language Models

ChildDiffusion: Unlocking the Potential of Generative AI and Controllable Augmentations for Child Facial Data Using Stable Diffusion and Large Language Models

Ensuring the availability of child facial datasets is essential for advancing AI applications, yet legal, ethical, and data scarcity concerns pose significant challenges. Current generative models such as StyleGAN excel at producing synthetic facial data but struggle with temporal consistency, contr...

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Bibliographic Details
Main Authors: Muhammad Ali Farooq, Wang Yao, Peter Corcoran
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
T21
stable diffusion
synthetic data
GAN’s
generative AI
diffusion models
Online Access:https://ieeexplore.ieee.org/document/11021410/
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https://ieeexplore.ieee.org/document/11021410/

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