However, as the generator becomes more skilled at producing realistic images, it often becomes less capable of generating surprising images. This is because the generator tends to learn the modes of the training data distribution and produces images that are concentrated around these modes. As a result, generated images may lack diversity and surprise.
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[1] T. Karras, S. Laine, and T. Aila, "Stylegan2: Analysis and optimization of the stylegan2 image synthesis algorithm," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020. However, as the generator becomes more skilled at
Depending on the setting, the noise level could be a consideration for some users. and T. Aila