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Project considered the problem of GAN-generated photorealistic, personalised facial models, that transfers a person's (source) facial expression movements to another person's (target) face for video generation

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DidaDidaDidaD/DeepFaceImageSynthesis

 
 

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DeepFakes

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We consider the problem of generating photorealistic, personalized head models, that capture mimics and speech expressions of a particular individual. Specifically, we focus on the task of face reenactment; that is, transferring a person's (source) facial expression movements to another person's (target) face. Having a wide range of applications, including virtual reality, film production, or video conferencing, various methods have been developed for the task, many of these utilizing Generative Adversarial Networks (GANs), and yielding impressive results.

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Project considered the problem of GAN-generated photorealistic, personalised facial models, that transfers a person's (source) facial expression movements to another person's (target) face for video generation

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  • Python 98.8%
  • Shell 1.2%