Age synthesis and age progression have many industrial and consumer applications:

• Cross-age face recognition: This can be incorporated into security applications, such as mobile device unlocking or desktop unlocking. The problem with current face recognition systems is that they need to be updated with time. With Age-cGAN networks, the lifespan of cross-age face recognition systems will be longer. 
• Finding lost children: This is an interesting application of an Age-cGAN. As the age of a child increases, their facial features change, and it becomes much harder to identify them. An Age-cGAN can simulate a person's face at a specified age.
• Entertainment: For example, in mobile applications, to show and share a friend's pictures at a specified age. 
• Visual effects in movies: It's a tedious and lengthy process to manually simulate a person's face when they are older. Age-cGANs can speed up this process and reduce the costs of creating and simulating faces.