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aitorzip avatar

aitorzip/PyTorch-CycleGAN

0
View on GitHub↗
1,321 stars·297 forks·Python·GPL-3.0·4 viewsarxiv.org/abs/1703.10593↗

PyTorch CycleGAN

A clean and readable Pytorch implementation of CycleGAN

Features

  • GANs, VAEs, and AEs - Listed in the “GANs, VAEs, and AEs” section of the The Incredible Pytorch awesome list.

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Open-source alternatives to PyTorch CycleGAN

Similar open-source projects, ranked by how many features they share with PyTorch CycleGAN.
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    1,548View on GitHub↗

    A pytorch implementation of Paper "Improved Training of Wasserstein GANs"

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    View on GitHub↗1,548
  • catalyst-team/gancatalyst-team avatar

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    View on GitHub↗5
  • csailvision/gandissectCSAILVision avatar

    CSAILVision/gandissect

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    Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/

    Pythondeep-learninggangenerative-adversarial-network
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  • ajbrock/biggan-pytorchajbrock avatar

    ajbrock/BigGAN-PyTorch

    2,924View on GitHub↗

    The author's officially unofficial PyTorch BigGAN implementation.

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See all 29 alternatives to PyTorch CycleGAN→

Frequently asked questions

What does aitorzip/pytorch-cyclegan do?

A clean and readable Pytorch implementation of CycleGAN

What are the main features of aitorzip/pytorch-cyclegan?

The main features of aitorzip/pytorch-cyclegan are: GANs, VAEs, and AEs.

What are some open-source alternatives to aitorzip/pytorch-cyclegan?

Open-source alternatives to aitorzip/pytorch-cyclegan include: caogang/wgan-gp — A pytorch implementation of Paper "Improved Training of Wasserstein GANs". catalyst-team/gan — Catalyst.GAN. csailvision/gandissect — Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/. dmitryulyanov/age — Code for the paper "Adversarial Generator-Encoder Networks". duanenielsen/deepinfomaxpytorch — Learning deep representations by mutual information estimation and maximization. ajbrock/biggan-pytorch — The author's officially unofficial PyTorch BigGAN implementation.