Generative Adversarial Networks

• According to Tech Target, Generative Adversarial Networks (GAN) is a "machine learning model in which two neural networks compete with each other to become more accurate in their predictions."
• GAN is used in a variety of ways that include photograph editing, face aging, photo blending, among many other uses.
• There are numerous repos and peer reviewed research papers on using GAN to manipulate facial attributes.

Repos

• Examples of repos on the use of GAN in the manipulation of facial attributes include:
•  SpatialAttentionGAN.
•  Gan-toolkit. 
•  Keras-GAN. 

Research Papers

• Examples of research papers on the use of GAN in the manipulation of facial attributes include:

• AttGAN: Facial Attribute Editing by Only Changing What You Want.
• Mask-aware Photorealistic Face Attribute Manipulation.
•  Semi-Latent GAN: Learning to generate and modify facial images from attributes.