Twin Auxiliary Classifier GAN

Requirements

• pytorch >=0.4.0
• torchvision ==0.2.0
• Jupyter Notebook

Datset

• A distribution of 1D MoG having three overlapping mixture components with modes at 0, 3, 6, and 110, and standard deviations of 1, 2, and 3, respectively.

Results

    [Left]: Result of Auxiliary Classifiers GAN                [Right]: Result of Twin Auxiliary Classifiers GAN

Todo List

• Implementing Projection cGAN.
• Implementing all the GANs with hinge loss.
• MMD evaluation for quantitative results.
• Experiments with CIFAR-100 and Overlapping MNIST

Acknowledgements

• https://github.com/wiseodd

• Twin Auxiliary Classifiers GAN. Mingming Gong*, Yanwu Xu*, Chunyuan Li, Kun Zhang, and Kayhan Batmanghelich. In Proceedings of 33rd Conference on Neural Information Processing Systems (NeurIPS 2019).(Spotlight).(https://arxiv.org/abs/1907.02690v2)