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Varuna Jayasiri
2021-01-23 16:28:50 +05:30
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docs/gan/cycle_gan.html
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<h1>Cycle GAN</h1>
<p>This is an implementation of paper
<a href="https://arxiv.org/abs/1703.10593">Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks</a>.</p>
<p>I&rsquo;ve taken pieces of code from <a href="https://github.com/eriklindernoren/PyTorch-GAN">https://github.com/eriklindernoren/PyTorch-GAN</a>.
<p>I&rsquo;ve taken pieces of code from <a href="https://github.com/eriklindernoren/PyTorch-GAN">eriklindernoren/PyTorch-GAN</a>.
It is a very good resource if you want to checkout other GAN variations too.</p>
<p>Cycle GAN does image-to-image translation.
It trains a model to translate an image from given distribution to another, say images of class A and B

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labml_nn/gan/cycle_gan.py
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This is an implementation of paper
[Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks](https://arxiv.org/abs/1703.10593).
I've taken pieces of code from [https://github.com/eriklindernoren/PyTorch-GAN](https://github.com/eriklindernoren/PyTorch-GAN).
I've taken pieces of code from [eriklindernoren/PyTorch-GAN](https://github.com/eriklindernoren/PyTorch-GAN).
It is a very good resource if you want to checkout other GAN variations too.
Cycle GAN does image-to-image translation.