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Because I have a limited memory GPU, I just can train model with small generator. But I don't enough understand about the difference between normal G and small G. Can you explain the main difference, please?
The text was updated successfully, but these errors were encountered:
StyleMapGAN-Light is 2.5X smaller than the original version. Stylemap resizer accounts for a large portion of
the network’s size, so we reduce the number of channels of feature maps in the stylemap resizer. The reconstruction
image lacks some detail, but StyleMapGAN-Light still outperforms baselines, and FIDlerp is even better than the original
version.
Because I have a limited memory GPU, I just can train model with small generator. But I don't enough understand about the difference between normal G and small G. Can you explain the main difference, please?
The text was updated successfully, but these errors were encountered: