DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks閱讀筆記
論文連接：https://arxiv.org/abs/1802.06454web 1、圖像翻譯 經過從一個圖像域到另外一個圖像域找到一些底層對應關係（例如，相似的語義）來學習映射函數，這就是圖像翻譯問題。翻譯的原則是保留源域的預期身份（例如，文本到圖像中的語義，面對動畫中的人類ID），同時生成與目標域的分佈匹配的樣本。網絡 2、目前技術挑戰 多年的研究已經在有足夠的配對的監督環境中產生了強大的翻譯
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相關文章
- 1. DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks閱讀筆記
- 2. DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks
- 3. Image-to-Image Translation with Conditional Adversarial Networks筆記
- 4. BEGAN: Boundary Equilibrium Generative Adversarial Networks閱讀筆記
- 5. Generative Adversarial Networks: An Overview文獻閱讀筆記
- 6. Self-Attention Generative Adversarial Networks
- 7. 【閱讀筆記】Generative Adversarial Nets
- 8. [論文筆記]Self-Attention Generative Adversarial Networks
- 9. SAGAN(Self-Attention Generative Adversarial Networks)論文筆記
- 10. SAGAN——Self-Attention Generative Adversarial Networks