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  # 2022-AdaIN-pytorch
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  This is an unofficial Pytorch implementation of the paper, `Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization, ICCV 2017` [arxiv](https://arxiv.org/abs/1703.06868). I referred to the [official implementation](https://github.com/xunhuang1995/AdaIN-style) in Torch. I used pretrained weights of vgg19 and decoder from [naoto0804](https://github.com/naoto0804/pytorch-AdaIN).
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  - [Pretrained weights](https://github.com/naoto0804/pytorch-AdaIN)
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  - List of all source URLs of images collected from the internet. [Image_sources.txt](https://github.com/media-comp/2022-AdaIN-pytorch/blob/main/Image_sources.txt)
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  - L. A. Gatys, A. S. Ecker, M. Bethge, A. Hertzmann, and E. Shechtman. Controlling perceptual factors in neural style transfer. In CVPR, 2017. [arxiv](https://arxiv.org/abs/1611.07865)
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- - A. Hertzmann. Algorithms for Rendering in Artistic Styles. PhD thesis, New York University, 2001.
 
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+ ---
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+ title: AdaIN Style Transfer
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+ sdk: gradio
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+ emoji: 🐨
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+ colorFrom: blue
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+ colorTo: indigo
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+ ---
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  # 2022-AdaIN-pytorch
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  This is an unofficial Pytorch implementation of the paper, `Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization, ICCV 2017` [arxiv](https://arxiv.org/abs/1703.06868). I referred to the [official implementation](https://github.com/xunhuang1995/AdaIN-style) in Torch. I used pretrained weights of vgg19 and decoder from [naoto0804](https://github.com/naoto0804/pytorch-AdaIN).
 
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  - [Pretrained weights](https://github.com/naoto0804/pytorch-AdaIN)
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  - List of all source URLs of images collected from the internet. [Image_sources.txt](https://github.com/media-comp/2022-AdaIN-pytorch/blob/main/Image_sources.txt)
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  - L. A. Gatys, A. S. Ecker, M. Bethge, A. Hertzmann, and E. Shechtman. Controlling perceptual factors in neural style transfer. In CVPR, 2017. [arxiv](https://arxiv.org/abs/1611.07865)
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+ - A. Hertzmann. Algorithms for Rendering in Artistic Styles. PhD thesis, New York University, 2001.