ATTRIBUTE-BASED FACE EDITING: AGING, EXPRESSION AND GENDER SWAP WITH GANS

This paper presented a GAN-based attribute editing framework for facial aging, expression modification, and gender transformation. By leveraging StyleGAN and latent space manipulation techniques, the system achieves high-quality and controllable face editing while maintaining identity consistency. Future research directions include improving attribute disentanglement using supervised and unsupervised techniques, integrating text-guided editing using multimodal models, reducing computational complexity for real-time applications, and enhancing fairness and bias mitigation in gender and age transformation tasks. Ethical considerations such as misuse prevention and watermarking of edited images should also be addressed in future implementations.  

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