ID-Preserving-Facial-Aging
What it is
This repository provides the official implementation for a paper on identity-preserving facial aging using Latent Diffusion Models. It fine-tunes Stable Diffusion with custom biometric, contrastive, and cosine losses to generate aged or de-aged versions of a specific individual's face while maintaining their identity.
The problem it solves
Standard text-to-image models often fail to preserve the unique identity of a specific individual when generating images with altered attributes like age, leading to inconsistent or unrecognizable results.
What you could use it for
- Generating realistic aged or de-aged portraits of a specific person for forensic or artistic purposes
- Researching identity preservation techniques in generative AI models
- Creating synthetic training data for age-invariant face recognition systems
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.