Conditional Generative Adversarial Networks（CGAN）笔记
1.概述 CGAN即条件对抗网络。GAN可以学习到训练样本的分布，从而生成新的数据。GAN虽然能生成新的数据，但是无法确切的控制新样本的类型。比如手写数字集，我们无法通过GAN来指定要生成的具体数字。条件对抗网络就是为了解决这个问题。 2. 理解CGAN 下面通过GAN 和CGAN的输入输出对比来理解CGAN. GAN: 生成器G, 输入一个噪声z， 输入一个图像G（Z） 判别器D, 输入一个图片
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相关文章
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