invertible Conditional GANs for image editing
github代码为https://github.com/Guim3/IcGAN 通常GAN的生成网络输入为一个噪声向量z,文献的创新点是,利用一个encoder网络,对输入图像提取得到一个特征向量z,将特征向量z,以及需要转换的目标attribute向量y串联输入生成网络,得到生成图像,网络结构如下, 如上图所示,包括连个encoder网络,分别为 Ez,Ey , Ez 用于将输入图像编码为特征向
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相关文章
- 1. [Style Transfer]——GANs for Medical Image Analysis
- 2. CGAN(conditional GANs)
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- 9. 【翻译】Image-to-Image Translation with Conditional Adversarial Networks
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