Conditional Generative Adversarial Networks（CGAN）筆記
1.概述 CGAN即條件對抗網絡。GAN可以學習到訓練樣本的分佈，從而生成新的數據。GAN雖然能生成新的數據，但是無法確切的控制新樣本的類型。比如手寫數字集，我們無法通過GAN來指定要生成的具體數字。條件對抗網絡就是爲了解決這個問題。 2. 理解CGAN 下面通過GAN 和CGAN的輸入輸出對比來理解CGAN. GAN: 生成器G, 輸入一個噪聲z， 輸入一個圖像G（Z） 判別器D, 輸入一個圖片
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相關文章
- 1. Conditional Generative Adversarial Nets（CGAN）
- 2. [GAN_papers]CGAN+Conditional Generative Adversarial Nets
- 3. Conditional Generative Adversarial Nets
- 4. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
- 5. Wasserstein Generative Adversarial Nets (WGAN ) and CGAN
- 6. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
- 7. 《Conditional Generative Adversarial Nets》論文解析
- 8. 論文筆記：Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation
- 9. Conditional adversarial networks
- 10. Bayesian Conditional Generative Adverserial Networks 論文筆記