Face Aging with Contextual Generative Adversarial Nets
网络结构如图2所示,首先按照68个人脸特征点对输入图像进行对齐,之后,采用Deeplab v2算法将输入图像分割为 人脸区域,和非人脸区域,并将非人脸区域标记为灰色. 生成网络-Transformer network 将处理后的图像,与年龄lable y y 输入到条件变换网络(G,Transformer),得到合成图像 G(x,y) G ( x , y ) (fake image). 生成网络结
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相关文章
- 1. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
- 2. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
- 3. Generative Adversarial Nets[BEGAN]
- 4. Generative Adversarial Nets[pix2pix]
- 5. Generative Adversarial Nets[CycleGAN]
- 6. Conditional Generative Adversarial Nets
- 7. Generative Adversarial Nets（译）
- 8. paper：Conditional Generative Adversarial Nets
- 9. Generative Adversarial Nets
- 10. cGAN:Conditional Generative Adversarial Nets