SAGAN(Self-Attention Generative Adversarial Networks)論文筆記
論文鏈接：Self-Attention Generative Adversarial Networks 這篇論文是將自注意力機制引入生成對抗網絡用於圖像生成任務。 摘要： 這篇論文，作者提出了自注意力生成對抗網絡(SAGAN)來建模像素間的遠距離關係，用於圖像生成任務。傳統的生成對抗網絡(GAN)生成高分辨率圖像的細節僅僅利用了低分辨率特徵圖的局部空間信息。在SAGAN，會利用特徵圖上所有的位置信
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相關文章
- 1. [論文筆記]Self-Attention Generative Adversarial Networks
- 2. Generative Adversarial Nets論文筆記
- 3. 論文筆記：Generative Adversarial Nets
- 4. Conditional Generative Adversarial Networks（CGAN）筆記
- 5. 論文譯文《ANOMALY DETECTION WITH GENERATIVE ADVERSARIAL NETWORKS》
- 6. Self-Attention Generative Adversarial Networks 論文解讀
- 7. Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks論文筆記
- 8. 論文筆記：Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation
- 9. 論文筆記--CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation
- 10. 論文閱讀筆記《Generative Adversarial Residual Pairwise Networks for One Shot Learning 》