Building Face Ageing Model Using Face Synthesis

Advancements in face synthesis technology have enabled innovative methods for modeling facial aging. Additionally, we address ethical considerations, proposing guidelines for responsible use.

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• 1 This research paper focuses primarily on creating a robust face aging model using deep learning and Generative Adversarial Networks (GANs), trained on a diverse dataset of facial images.
• 2 The proposed approach captures both global features and local textures to produce realistic age-progressed images while preserving the subject's identity.
• 3 This paper also examines face synthesis techniques, with specific emphasis for the various practical usage of GANs.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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