StackGAN（2017）: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks 簡述： 從文本描述中合成高質量的圖像是計算機視覺中的一個具有挑戰性的問題，具有許多實際應用。現有的文本-圖像方法生成的樣本可以大致反映給定描述的含義，但無法包含必要的細節和生動的對象部分。在這篇論文中，我們提出堆疊式生成性對抗網路
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相關文章
- 1. StackGAN++《StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks》探析
- 2. Generative Adversarial Text to Image Synthesis
- 3. 論文閱讀筆記一【StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Netwo】
- 4. text to image（二）:《Generative Adversarial Text to Image Synthesis》
- 5. Generative Adversarial Text to Image Synthesis 論文解讀
- 6. StackGAN++: Realistic Image Synthesiswith Stacked Generative Adversarial Networks 論文解讀
- 7. AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
- 8. DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis 論文解讀
- 9. 《Generative Adversarial Text to Image Synthesis》閱讀理解
- 10. text to image（九）:《Photographic Text-to-Image Synthesis with a Hierarchically-nested Adversarial Ne 》