MirroGAN: Learning Text-to-image Generation by Redescription
MirroGAN: Learning Text-to-image Generation by Redescription 摘要 儘管 GAN 已經能夠生成非常逼真的高分辨率圖片了, 但是要確保生成的圖片和文本語義的一致還是一個很有挑戰性的問題. 爲了解決這個問題, 作者提出了 MirroGAN (a novel global-local attentive and semantic-preserv
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相關文章
- 1. Feature Generation by CNN (FGCNN)
- 2. Deep Reinforcement Learning for Dialogue Generation
- 3. 5.Conditional Generation by RNN & Attention(李宏毅)
- 4. 李宏毅ML lecture-17-18 unsupervised Learning Generation
- 5. 論文閱讀：Sequence Generation by Editing Prototype
- 6. Learning by doing
- 7. Adversarial Learning for Neural Dialogue Generation 代碼分析
- 8. Image Cption：Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation
- 9. Reinforcement Learning: Planning by DP
- 10. Assembly Language Learning (by Joshua)