Turning Photos into Paintings using Neural Networks
00:00 Intro 00:38 Unpaired Image Translation 01:02 CycleGAN Overview 01:44 Shortcomings of CycleGAN 02:38 CycleGAN, a Master of Steganography 03:30 Contrast...
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About this video
00:00 Intro
00:38 Unpaired Image Translation
01:02 CycleGAN Overview
01:44 Shortcomings of CycleGAN
02:38 CycleGAN, a Master of Steganography
03:30 Contrastive Learning for Unpaired Image-to-Image Translation
05:40 Turning Photos into Paintings
07:15 AI Art
08:31 Bloopers
Contrastive Unpaired Translation Official Repository
https://github.com/taesungp/contrastive-unpaired-translation
Contrastive Learning for Unpaired Image-to-Image Translation (Paper)
https://arxiv.org/pdf/2007.15651.pdf
CycleGAN Homepage
https://junyanz.github.io/CycleGAN/
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks (Paper)
https://arxiv.org/pdf/1703.10593.pdf
CycleGAN, a Master of Steganography (Paper)
https://arxiv.org/pdf/1712.02950.pdf
WikiArt
https://www.wikiart.org/
My AI Art Instagram Account
https://www.instagram.com/leoisikdogan/
My AI Art YouTube Channel
https://www.youtube.com/channel/UCqLL4GQlrjYNucDp6BfbEuQ
Video Information
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7.0K
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Duration
8:46
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Published
Feb 22, 2021
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hd
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This video is tagged with the following topics. Click any tag to explore more related content and discover similar videos:
#digital image #computer science #image processing #image and video processing #deep learning #cyclegan #contrastive unpaired translation #ai art #style transfer #artificial intelligence #image filter #generative adversarial networks #digital painting #new media #machine learning #gan #neural network #neural filter #image translation #cycle consistency #generative #Unpaired Image-to-Image Translation #Cycle-Consistent Adversarial Networks #Contrastive Learning
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