论文笔记：Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation
本文提出了一个比较有趣的 Z S D A ZSDA ZSDA（zero-shot domain adaptation） 的学习策略。 假如现在我们有两个 U I T ( S t y l e T r a n s f e r ) UIT(Style~Transfer) UIT(Style Transfer) 的任务， 原本我们可以构建两个 C y c l e G A N CycleGAN Cycl
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相关文章
- 1. 【论文笔记 CVPR-2019】《Domain-Symmetric Networks for Adversarial Domain Adaptation》
- 2. Conditional Generative Adversarial Networks（CGAN）笔记
- 3. [cvpr2017]Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks
- 4. Domain Adaptation 与 Generative Adversarial Network
- 5. [解读] Coupled Generative Adversarial Networks
- 6. (CVPR 2019)Domain-Symmetric Networks for Adversarial Domain Adaptation笔记
- 7. Bayesian Conditional Generative Adverserial Networks 论文笔记
- 8. [论文笔记]Self-Attention Generative Adversarial Networks
- 9. SAGAN(Self-Attention Generative Adversarial Networks)论文笔记
- 10. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS