StarGAN（2018）: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation 简述： 现有的方法在两个以上的领域中具有有限的可扩展性和鲁棒性，因为不同的模型应该为每一对图像域独立地建立。为了解决这一限制，本文提出了StarGAN，可以仅使用一个模型在多个域中执行图像到图像的转换。starga
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相关文章
- 1. StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation（CVPR18）
- 2. StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
- 3. CartoonGAN: Generative Adversarial Networks for Photo Cartoonization
- 4. [ICCV2019] Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation
- 5. Binary Generative Adversarial Networks for Image Retrieval
- 6. Generative Adversarial Networks for Hyperspectral Image Classification
- 7. Graphical Generative Adversarial Networks
- 8. Triangle Generative Adversarial Networks
- 9. Contrastive Generative Adversarial Networks
- 10. Generative Adversarial Networks overview（1）