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Tensorflow implementation related to my research
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All implementation is based on DCGAN arcitecture (https://arxiv.org/abs/1511.06434)
- RFGAN (Improved Training of Generative Adversarial Networks using Representative Features)
- ResembledGAN (Resembled Generative Adversarial Networks: Two Domains with Similar Attributes)
- MGGAN (MGGAN: Solving Mode Collapse using Manifold Guided Training)
- Recycling discriminator (Recycling the Discriminator for Improving the Inference Mapping of GAN)
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Running
- This code is based on CelebA (64 x 64 x 3) dataset
- python main.py --gan_type <Type> --dataset <Dataset> --epoch <Epoch> --batch_size <Batch_size>
- Gan Type: RFGAN, ResembledGAN, MGGAN, Recycling_discriminator
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Requiisites
- Python 2.7
- Tensorflow 0.18
- Scipy
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Code Reference
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QuickSolverDab/Tensorflow-MyGANs
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