FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
相关介绍 Face aging又叫age synthesis和age progression。主要的应用领域包括跨年龄识别，寻找丢失儿童和娱乐。传统的人脸老化包括两种，基于原型设计方法和基于模型的方法。基于原型的方法在分好的年龄组里面求平均人脸，利用这些普遍变化进行人脸的老化处理。简单快速但是但是会产生不真实的图片。相反，基于模型的方法使用模型计算个体老化的机械化变化，如肌肉，皮肤和头盖骨方面的改
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相关文章
- 1. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
- 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）笔记
- 6. [GAN_papers]CGAN+Conditional Generative Adversarial Nets
- 7. C-GAN(2014):Conditional Generative Adversarial Nets
- 8. 论文阅读——《Conditional Generative Adversarial Nets》
- 9. [论文笔记]Improving Heterogeneous Face Recognition with Conditional Adversarial Networks
- 10. 《Conditional Generative Adversarial Nets》论文解析