Generative Adversarial Networks

Goals

To find information on the use of Generative Adversarial Networks in changing facial attributes such as closing eyes and changing facial expressions on demand in a photo-realistic way.

Early Findings

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

Research Papers

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

Proposed next steps:

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