Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks論文筆記
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks論文筆記 作者將生成器網絡和判別式網絡組合到了一起組成了一個生成對抗網絡。MDANs和MGANs的區別在於MDANs因爲迭代優化，所以能創建更自然的背景，能更好地保存好輸入圖片的內容，MGANs則用來訓練很多圖片，所以它能學到很
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相關文章
- 1. 論文譯文《ANOMALY DETECTION WITH GENERATIVE ADVERSARIAL NETWORKS》
- 2. [論文筆記]Self-Attention Generative Adversarial Networks
- 3. SAGAN(Self-Attention Generative Adversarial Networks)論文筆記
- 4. 論文筆記：Eye In-Painting with Exemplar Generative Adversarial Networks
- 5. High Quality Facial Surface and Texture Synthesis via Generative Adversarial Networks
- 6. Generative Adversarial Text to Image Synthesis 論文解讀
- 7. Generative Adversarial Nets論文筆記
- 8. 論文筆記：Generative Adversarial Nets
- 9. Generative Adversarial Text to Image Synthesis
- 10. Conditional Generative Adversarial Networks（CGAN）筆記