Conditional adversarial networks
GAN網絡在訓練生成模型受到了廣泛的青睞，文章介紹一個具有條件限制的GAN網絡，通過簡單的添加額外輸入數據，來構建我們所需要的條件化的生成器和判別器。文章表明，該模型可以用於學習多模態模型，通過提供了圖像標記應用程序的初步示例，演示了該方法如何生成不屬於訓練標籤的描述性標籤。 生成式對抗網絡近期作爲訓練生成模型的替代框架，以迴避近似許多棘手概率計算問題的困難。 對抗網絡的優點是不需要馬可夫鏈，只需
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相關文章
- 1. Conditional Generative Adversarial Networks（CGAN）筆記
- 2. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
- 3. (Pixel2PixelGANs)Image-to-Image translation with conditional adversarial networks
- 4. Image-to-Image Translation with Conditional Adversarial Networks
- 5. Image-to-Image Translation with Conditional Adversarial Networks筆記
- 6. Image-to-Image Translation with Conditional Adversarial NetWorks 翻譯
- 7. 【翻譯】Image-to-Image Translation with Conditional Adversarial Networks
- 8. pix2pix（2017）：Image-to-Image Translation with Conditional Adversarial Networks
- 9. Conditional Generative Adversarial Nets
- 10. Conditional Generative Adversarial Nets（CGAN）