FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
文章用於生成不同年齡的圖片,採用的模型是條件對抗網絡,主要創新點是,首先通過一個網絡,提取圖像特徵向量,並通過身份保持網絡,優化圖像的特徵向量,特到特徵向量 z∗ ,之後便可以對於每個輸入年齡,查找其年齡向量,並將該年齡向量與輸入圖片特徵向量 z∗ 串聯,輸入生成網絡,生成目標年齡圖片. 特徵向量優化網絡結構如下, 網絡的訓練數據爲,輸入圖像x,以及該圖像的年齡 y0 ,對輸入圖像,將其輸入Enc
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- 1. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
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相關文章
- 1. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
- 2. Face Aging with Contextual Generative Adversarial Nets
- 3. Conditional Generative Adversarial Nets
- 4. Conditional Generative Adversarial Nets（CGAN）
- 5. Conditional Generative Adversarial Networks（CGAN）筆記
- 6. [GAN_papers]CGAN+Conditional Generative Adversarial Nets
- 7. C-GAN(2014):Conditional Generative Adversarial Nets
- 8. 論文閱讀——《Conditional Generative Adversarial Nets》
- 9. [論文筆記]Improving Heterogeneous Face Recognition with Conditional Adversarial Networks
- 10. 《Conditional Generative Adversarial Nets》論文解析