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SinGAN: Learning a Generative Model from a Single Natural Image: Difference between revisions
SinGAN: Learning a Generative Model from a Single Natural Image (view source)
Revision as of 19:01, 15 November 2019
, 15 November 2019→Architecture
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==Architecture== | ==Architecture== | ||
They build <math>N</math> GANs | They build <math>N</math> GANs, N usually 7-8<br> | ||
Each GAN <math>G_n</math> adds details to patches of the image produced by GAN <math>G_{n+1}</math> below it.<br> | Each GAN <math>G_n</math> adds details to patches of the image produced by GAN <math>G_{n+1}</math> below it.<br> | ||
The final GAN <math>G_0</math> adds only fine details. | The final GAN <math>G_0</math> adds only fine details. | ||
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The architecture is the same as the generator.<br> | The architecture is the same as the generator.<br> | ||
The patch size is <math>11 \times 11</math> | The patch size is <math>11 \times 11</math> | ||
==Training and Loss Function== | ==Training and Loss Function== | ||