Deep Generative Models Course Project at TU Darmstadt
Deep Generative Models Course Project at TU Darmstadt.
The main goal of this project is to learn a conditional GAN that can interpolate between different types of food. We want to achieve fluid transitions between e.g.:
Video results can be found here.
The code is based on a PyTorch implementation of Improved Training of Wasserstein GAN and a PyTorch implementation of Progressive Growing of GANs
React
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