Learning Residual Images for Face Attribute Manipulation
Wei Shen， Rujie Liu Fujitsu Research & Development Center, Beijing, China. @CVPR2017 Introduction 作者提出想要對人臉的一些屬性進行操控，結合生成模型來完成. 當前主流的生成模型包括GAN以及VAE，但由於GAN模型是接收隨機噪聲來生成圖片，因此無法對圖片進行編碼.而VAE的編碼-解碼結構也會對圖像的重
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相關文章
- 1. SaGAN:Generative Adversarial Network with Spatial Attention for Face Attribute Editing
- 2. Learning to Detect Fake Face Images in the Wild
- 3. ResNet--Deep Residual Learning for Image Recognition
- 4. [ResNet]Deep Residual Learning for Image Recognition
- 5. Deep Residual Learning for Image Recognition
- 6. ResNet —— Deep Residual Learning for Image Recognition
- 7. Deep Residual Learning for Image Recognition （zh）
- 8. CREST: Convolutional Residual Learning for Visual Tracking
- 9. ResNet(deep residual learning for image recognition)
- 10. ResNet——Deep Residual Learning for Image Recognition