CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation

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Deep Learning CDGAN
Overview

CDGAN

CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation

CDGAN Implementation in PyTorch

This is the implementation of our paper called "CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation". https://arxiv.org/abs/2001.05489.

CDGAN Architectue




Acknowledgments

  • We gratefully acknowlege the NVIDIA Corp. for donating us the NVIDIA GeForce Titan X Pascal GPU used for this research.

  • code is heavily borrowed from CycleGAN Paper pytorch-CycleGAN.
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Comments
  • How to run the code

    How to run the code

    Hi, thanks for contrubuting the papers. According to images shown there, CDGAN has more accuracy over other methods (seems even better than pix2pixhd) and I wish I could try it on my PC, but I don't get how to run the code. Can you, please, provide the folder and file structure for datasets? (shall it be paired or contained in 2 different folders) And also, is it possible to run code on resolutions 256 or 512 squares? Seems that paper contains only 128 pixels images. Thanks.

    opened by kex243 0
Owner
Kancharagunta Kishan Babu
PhD Student, Computer Vision Group
Kancharagunta Kishan Babu
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