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Tutorial introduction slides to GANs. Code implementations and links of relevant papers.

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GANs

Repository papers and code on different GAN models.

This [slides] are tutorial introduction for GANs covering the following topics:

  • GANs:
    • Model.
    • Zero-Sum Game and Nash Equilibrium.
    • Optimal Point.
    • Maximum Likelihood Models vs GANs.
    • GAN Problems.
    • Evaluation.
  • Models:
    • DCGAN.
    • WGAN/WGAN-GP.
    • SNGAN.
    • ProGAN.
    • Conditional GANs.
    • SAGAN.
    • BigGAN.

The plan is to include in the future other models and relevant papers:

  • InfoGAN
  • Unrolled GANs
  • RSGAN/RASGAN
  • Two Time-Scale Update Rule
  • StyleGAN
  • CycleGAN
  • Is Generator Conditioning Causally Related to GAN Performance?

Papers:

  • Original GAN: 'Generative Adversarial Networks' Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio. 2014. [Arxiv].

  • DCGAN: 'Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks' Alec Radford, Luke Metz, Soumith Chintala. 2016. [Arxiv]. [Code].

  • InfoGAN: 'InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets' Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel. 2016. [Arxiv]. [Code].

  • LSGAN: 'Least Squares Generative Adversarial Networks' Xudong Mao, Qing Li, Haoran Xie, Raymond Y.K. Lau, Zhen Wang, Stephen Paul Smolley. 2017. [Arxiv]. [Code].

  • WGAN: 'Wassertein GAN' Martin Arjovsky, Soumith Chintala, Léon Bottou. 2017. [Arxiv]. [Code].

  • WGAN-GP: 'Improved Training of Wasserstein GANs' Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, Aaron Courville. 2017. [Arxiv]. [Code].

  • RSGAN & RaSGAN: 'The relativistic discriminator: a key element missing from standard GAN' Alexia Jolicoeur-Martineau. 2018. [Arxiv]. [RaSGAN Code]. [RaLSGAN Code]. [RaSGAN-GP Code].

  • Spectral Normalization GAN: 'Spectral Normalization for Generative Adversarial Networks' Takeru Miyato, Toshiki Kataoka, Masanori Koyama, Yuichi Yoshida. 2018. OpenReview. [Code].

  • Self Attention GAN: 'Self-Attention Generative Adversarial Networks' Han Zhang, Ian Goodfellow, Dimitris Metaxas, Augustus Odena. 2018. [Arxiv] [Code]

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