diff --git a/README.md b/README.md index ddae7ce..b43a789 100644 --- a/README.md +++ b/README.md @@ -3,27 +3,18 @@ A curated list of GAN & Deepfake papers and repositories. ## GANs -- Vanilla GAN [(paper)](https://arxiv.org/abs/1406.2661) - * Implementations - * PyTorch - * [https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/gan] - * [https://github.com/devnag/pytorch-generative-adversarial-networks] - * [https://github.com/shivakanthsujit/GAN-PyTorch] - * Keras - * [https://github.com/eriklindernoren/Keras-GAN/tree/master/gan] - * [https://github.com/osh/KerasGAN] - * [https://github.com/jason71995/Keras-GAN-Library] - * [https://github.com/Zackory/Keras-MNIST-GAN] -- DCGAN [(paper)](https://arxiv.org/abs/1511.06434) - * Implementations - * PyTorch - * [https://github.com/znxlwm/pytorch-MNIST-CelebA-GAN-DCGAN] - * [https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/dcgan] - * Keras - * [https://github.com/jacobgil/keras-dcgan] - * [https://github.com/eriklindernoren/Keras-GAN/blob/master/dcgan/dcgan.py] - * [https://github.com/mitchelljy/DCGAN-Keras] - + +### Unconditional GANs ++ Vanilla GAN: Generative Adversarial Networks, [[paper]](https://arxiv.org/abs/1406.2661), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/gan) ++ DCGAN: Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, [[paper]](https://arxiv.org/abs/1511.06434), [[github]](https://github.com/carpedm20/DCGAN-tensorflow) + +### Conditional GANs ++ CGAN: Conditional Generative Adversarial Nets, [[paper]](https://arxiv.org/abs/1411.1784), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/blob/master/implementations/cgan/cgan.py) ++ ACGAN: Conditional Image Synthesis With Auxiliary Classifier GANs, [[paper]](https://arxiv.org/abs/1610.09585), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/blob/master/implementations/acgan/acgan.py) + +### Image-to-Image Translation ++ CycleGAN: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks, [[paper]](https://arxiv.org/abs/1703.10593), [[github]](https://github.com/junyanz/CycleGAN) + ## Applications using GANs ### Anime generator