DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis 論文解讀
這是一篇CVPR 2019的一篇文章，思想簡單，但是實驗結果是真的簡單，服！服！服！！！（但是我爲什麼想不到呢？我太菜）。文章中介紹了很多模塊，也介紹了文章idea的來源，爲此我還看了相關的Memory Networks及各種變形（對理解本篇DM-GAN其實用處不大，但是這些論文挺好的，推薦一看。） 論文: https://arxiv.org/abs/1904.01310?context=cs.
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相關文章
- 1. Generative Adversarial Text to Image Synthesis 論文解讀
- 2. Generative Adversarial Network Architectures For Image Synthesis Using Capsule Networks
- 3. Self-Attention Generative Adversarial Networks 論文解讀
- 4. [解讀] Coupled Generative Adversarial Networks
- 5. GAN系列：論文閱讀——MSGAN(Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis)
- 6. Generative Adversarial Text to Image Synthesis
- 7. 【論文閱讀】CartoonGAN: Generative Adversarial Networks for Photo Cartoonization
- 8. CartoonGAN: Generative Adversarial Networks for Photo Cartoonization
- 9. CPGAN: Full-Spectrum Content-Parsing Generative Adversarial Networks for Text-to-Image Synthesis
- 10. [Style Transfer]——Blood Vessel Geometry Synthesis using Generative Adversarial Networks