pix2pix Image-to-Image Translation with Conditional Adversarial Networks笔记及代码实现
1.Introduction GANs在最近两年得到了广泛的应用，本文研究的技术很多人就已经提到过，尽管如此，之前的论文都是关注特定的应用，而cGANs作为图像转换的问题的通用方法的有效性仍然是不清楚的，我们的主要贡献 在于阐释了cGANs在很多问题上都能产生合理的结果，第二个贡献在于提出来一个简单有效的框架，并分析了几种结构的选择结果 2.Related work 2.1图像建模的结构化损失
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相关文章
- 1. pix2pix（2017）：Image-to-Image Translation with Conditional Adversarial Networks
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- 4. Image-to-Image Translation with Conditional Adversarial Networks论文阅读分享(pix2pix)
- 5. 【翻译】Image-to-Image Translation with Conditional Adversarial Networks
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- 9. 《Image-to-Image Translation with Conditional Adversarial Networks》论文总结
- 10. 全文翻译&杂记《Image-to-Image Translation with Conditional Adversarial NetWorks》