EE608-Project

This course project entails a comparitive study of how the results vary when discriminator sees differently pre-processed images from the dataset(s). These pre-processings will be low-level digital image processing algorithms which this course is centered around.

Papers Replicated:

1. GAN
2. DCGAN
3. WGAN
4. WGAN-GP
5. SRGAN
6. infoGAN
7. RealnessGAN
8. Cycle-GAN + Style-GAN
9. pix2pix

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Datasets Used:

1. MNIST
2. Fashion-MNIST
3. AFHQ (Dog Subset)
4. Facades
5. SR-Kaggle

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Framework(s) Used:

PyTorch Lightning + WandB

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++ Literature Survey/Review

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Aryan Garg
B19153