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Highly scalable Apache MXNet based implementation of various Generative Adversarial Networks.

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Apache MXNet Gluon - Generative Adversarial Networks (GAN)

Collection of Jupyter Notebooks with Apache MXNet GLUON implementation of various standard GAN papers.

Note: At this point of time, this repo may be used as reference implementations only. Hyperparameters, and various other factors are not fully tuned. Accuracies/any metric claimed in paper may NOT be exactly reflected with this implementations.

Prerequisites

pip install mxnet-mkl # For CPU machines
pip install mxnet-cu90mkl # For GPU machines

GAN Networks

No. Title Paper Code
1 Generative Adversarial Networks (GAN) https://arxiv.org/abs/1406.2661 GAN
2 Deep Convolutional GAN (DCGAN) https://arxiv.org/abs/1511.06434 TODO
3 Conditional GAN (CGAN) https://arxiv.org/abs/1411.1784 TODO
4 Pix2Pix https://arxiv.org/abs/1611.07004 TODO
5 BEGAN: Boundary Equilibrium Generative Adversarial Networks https://arxiv.org/abs/1703.10717 TODO
6 BicycleGAN: Toward Multimodal Image-to-Image Translation https://arxiv.org/abs/1711.11586 TODO
7 Boundary seeking GAN https://arxiv.org/abs/1611.06430 TODO
8 Context Conditional GAN https://arxiv.org/abs/1611.06430 TODO
9 Context Encoders: Feature Learning by Inpainting https://arxiv.org/abs/1604.07379 TODO
10 Coupled Generative Adversarial Networks https://arxiv.org/abs/1606.07536 TODO
11 Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks https://arxiv.org/abs/1703.10593 TODO
12 DiscoGAN - Learning to Discover Cross-Domain Relations with Generative Adversarial Networks https://arxiv.org/abs/1703.05192 TODO
13 DualGAN: Unsupervised Dual Learning for Image-to-Image Translation https://arxiv.org/abs/1703.05192 TODO
14 Energy-based Generative Adversarial Network https://arxiv.org/abs/1609.03126 TODO
15 InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets https://arxiv.org/abs/1606.03657 TODO
16 Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks https://arxiv.org/abs/1612.05424 TODO
17 StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation https://arxiv.org/abs/1711.09020 TODO
18 SRGAN: Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network https://arxiv.org/abs/1609.04802 TODO
19 Improved Training of Wasserstein GANs https://arxiv.org/abs/1704.00028 TODO

Contributions

All contributions welcome! You can contribute with bug fixes, changes, suggestions for new paper implementations. Please see above list of GAN networks I plan to implement, please feel free to create an issue and assign yourself any implementation.

See this issue with list of TODOs enhancements planned - #1

Credits, Motivation

  1. This work is heavily motivated and influenced from this awesome project - https://github.com/eriklindernoren/keras-gan

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