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Neural Network Learns to Synthetically Age Faces, and Make Them Look Younger, Too

2019.01.18|
Deep Learning

Enter Grigory Antipov from Orange Labs in France and a couple of pals who have developed a deep-learning machine that can do the job with ease. Not only can their system make young faces look older, it can make older faces look younger.

A couple of recent developments have made their task easier. In recent years, computer scientists have built deep-learning machines that are able to modify faces in various different but realistic ways. This approach can create realistic synthetic faces that look older.

However, there is a problem. In making faces look older, these deep-learning machines often lose the person’s identity in the process. So the individual looks older but can no longer be identified.

Antipov and co have come up with a way to solve that problem. Their approach involves two deep-learning machines that work together—a face generator and a face discriminator. Both machines learn what faces look like as they age by analyzing photographs of people in the age groups 0-18, 19- 29, 30-39, 40-49, 50-59, and 60+ years old.

In total, the machines were trained on 5,000 faces in each group taken from the Internet Movie Database and from Wikipedia and then labeled with the person’s age. In this way, the machine learns the characteristic signature of faces in each age group. It is this abstract signature that the face generator can then apply to other faces to make them look the same age.

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