对抗学习之Learning from Simulated and Unsupervised Images through Adversarial Training
今天讲一篇cvpr2017的best paper，不是大家熟知的densely connect，是苹果的Learning from Simulated and Unsupervised Images through Adversarial Training，用GAN来做对抗学习的。 Motivation： 搞数据一直是深度学习的老大难问题，也是工业界优势于学术界的地方，需要花钱标很多数
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相关文章
- 1. 【paper 2】Learning from Simulated and Unsupervised Images through Adversarial Training
- 2. Learning from Simulated and Unsupervised Images through Adversarial Training：解析simGAN
- 3. 论文笔记（三） 【Learning from Simulated and Unsupervised Images through Adversarial Training】
- 4. CS231n Lecture 16 | Adversarial Examples and Adversarial Training
- 5. [论文翻译]Intramodality Domain Adaptation Using Self Ensembling and Adversarial Training
- 6. Beyond Narrative Description: Generating Poetry from Images by Multi-Adversarial Training
- 7. GAIL生成对抗模仿学习详解《Generative adversarial imitation learning》
- 8. Supervised learning and Unsupervised learning
- 9. 资源|17类对抗网络经典论文及开源代码（附源码）
- 10. Learning Deep Learning（学习深度学习）