论文笔记--CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation
CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation 用于图像到图像转换的周期-合成GAN 摘要：图像到图像变换的主要目的是将一个域的图像转换为另一个域。大部分的研究都集中在一组预定义域的图像变换问题上。很少有研究报告为不同领域的图像到图像转换开发了一个通用的框架。随着
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相关文章
- 1. CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation
- 2. [论文笔记]Self-Attention Generative Adversarial Networks
- 3. SAGAN(Self-Attention Generative Adversarial Networks)论文笔记
- 4. 论文笔记：Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation
- 5. 论文阅读笔记《Generative Adversarial Residual Pairwise Networks for One Shot Learning 》
- 6. Generative Adversarial Nets论文笔记
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- 8. Conditional Generative Adversarial Networks（CGAN）笔记
- 9. 论文笔记《Adversarial Networks for Prostate Cancer Detection》
- 10. Binary Generative Adversarial Networks for Image Retrieval