Semi-supervised Conditional GANs
We introduce a new model for building conditional generative models in a semi-supervised setting to conditionally generate data given attributes by adapting the GAN framework. The proposed semi-supervised GAN (SS-GAN) model uses a pair of stacked discriminators to learn the marginal distribution of the data, and the conditional distribution of the attributes given the data respectively... (read more)
PDFTasks
CIFAR-10
CelebA
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Methods used in the Paper
| METHOD | TYPE | |
|---|---|---|
Convolution
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Convolutions | |
GAN
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Generative Models |