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 簡述： 現有的方法在兩個以上的領域中具有有限的可擴展性和魯棒性，因爲不同的模型應該爲每一對圖像域獨立地建立。爲了解決這一限制，本文提出了StarGAN，可以僅使用一個模型在多個域中執行圖像到圖像的轉換。starga
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相關文章
- 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）