![]() ![]() Until recently, video content has been more difficult to alter in any substantial way. Conversely, as the discriminator gets better at spotting fake video, the generator gets better at creating them. Once the generator begins creating an acceptable level of output, video clips can be fed to the discriminator.Īs the generator gets better at creating fake video clips, the discriminator gets better at spotting them. The first step in establishing a GAN is to identify the desired output and create a training dataset for the generator.
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