The project transforms input images into Claude Monet-style artwork using GANs, generating 7,000-10,000 images. It uses a generator and discriminator, assessed with MiFID. DualGAN and CycleGAN models were enhanced, with CycleGAN plus Inception blocks achieving the best FID score of 109. Future work will explore GANILLA for further improvements.
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The project transforms input images into Claude Monet-style artwork using GANs, generating 7,000-10,000 images. It uses a generator and discriminator, assessed with MiFID. DualGAN and CycleGAN models were enhanced, with CycleGAN plus Inception blocks achieving the best FID score of 109. Future work will explore GANILLA for further improvements.
Adil1567/Kaggle-Using-GANs-to-Create-Art
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The project transforms input images into Claude Monet-style artwork using GANs, generating 7,000-10,000 images. It uses a generator and discriminator, assessed with MiFID. DualGAN and CycleGAN models were enhanced, with CycleGAN plus Inception blocks achieving the best FID score of 109. Future work will explore GANILLA for further improvements.
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