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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 21:52, 13 January 2020
, 13 January 2020→Architecture
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They use 32 kernels per block at the coarsest scale and increase <math>2 \times</math> every 4 scales.<br> | They use 32 kernels per block at the coarsest scale and increase <math>2 \times</math> every 4 scales.<br> | ||
===[https://arxiv.org/pdf/1502.03167.pdf Batch Normalization]=== | ====[https://arxiv.org/pdf/1502.03167.pdf Batch Normalization]==== | ||
; Definitions: | ; Definitions: | ||
* Internal Covariate Shift - the change in distribution of network activations as network parameters change. | * Internal Covariate Shift - the change in distribution of network activations as network parameters change. | ||