Class-Conditional Superresolution with GANs
See full paper here.
See each folder's
README.md files for more details.
Experiments with original super-resolution baseline implementation.
Experiments using MNIST dataset, primarily for conditional-GAN implementation.
Experiments using celebA dataset, primarily for GAN + class loss implementation.
Classifier trained to recognize attributes of
celebA dataset, whose weights are saved for classifier loss model.