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[Open Sourced] StyleSwin: CVPR 2022 Transformer Based GAN for High Resolution Image Generation Paper Implementation by Microsoft Research Asia

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Bowen Zhang, Shuyang Gu, Bo Zhang, Jianmin Bao, Dong Chen, Fang Wen, Yong Wang, Baining Guo

CVPR 2022

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This folder provides a re-implementation of this paper in PyTorch, developed as part of the course METU CENG 796 - Deep Generative Models. The re-implementation is provided by:

We have already trained several models and we have saved the best ones in the following drive directory where there are 2 models: one for LSUN and one for CELEBA. https://drive.google.com/drive/folders/1MlT53Woi5pRLNGUBG0Pfvx9ximXxCojR?usp=sharing You can also load your own trained model by setting the correct path for the model.

Please see the jupyter notebook file main.ipynb for a summary of paper, the implementation notes and our experimental results.

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[Open Sourced] StyleSwin: CVPR 2022 Transformer Based GAN for High Resolution Image Generation Paper Implementation by Microsoft Research Asia

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