GAN系列：Image-to-Image Translation with Conditional Adversarial Networks

时间 2020-12-30

标签 GAN 繁體版

原文原文链接

Abstract 1. image-to-image trainslation 存在的两个问题： 1）many-to-one:将照片映射为edges/segments/semantic labels 2）one-to-many:将labels/sparse user inputs映射为真实图片一般的做法是predict pixels form pixels；作者的创新点为develop a co

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1. pix2pix（2017）：Image-to-Image Translation with Conditional Adversarial Networks
2. Image-to-Image Translation with Conditional Adversarial Networks笔记
3. 【翻译】Image-to-Image Translation with Conditional Adversarial Networks
4. Image-to-Image Translation with Conditional Adversarial NetWorks 翻译
5. Image-to-Image Translation with Conditional Adversarial Networks
6. (Pixel2PixelGANs)Image-to-Image translation with conditional adversarial networks
7. 论文之Image-to-Image Translation with Conditional Adversarial Networks 2
8. pix2pix Image-to-Image Translation with Conditional Adversarial Networks笔记及代码实现
9. 全文翻译&杂记《Image-to-Image Translation with Conditional Adversarial NetWorks》
10. Image-to-Image Translation with Conditional Adversarial Networks 论文翻译
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1. pix2pix（2017）：Image-to-Image Translation with Conditional Adversarial Networks
2. Image-to-Image Translation with Conditional Adversarial Networks笔记
3. 【翻译】Image-to-Image Translation with Conditional Adversarial Networks
4. Image-to-Image Translation with Conditional Adversarial NetWorks 翻译
5. Image-to-Image Translation with Conditional Adversarial Networks
6. (Pixel2PixelGANs)Image-to-Image translation with conditional adversarial networks
7. 论文之Image-to-Image Translation with Conditional Adversarial Networks 2
8. pix2pix Image-to-Image Translation with Conditional Adversarial Networks笔记及代码实现
9. 全文翻译&杂记《Image-to-Image Translation with Conditional Adversarial NetWorks》
10. Image-to-Image Translation with Conditional Adversarial Networks 论文翻译

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