2019-ICCV最佳論文-SinGAN: Learning a Generative Model from a Single Natural Image
2019-ICCV最佳論文-SinGAN: Learning a Generative Model from a Single Natural Image 作者： Tamar Rott Shaham Tali Dekel Tomer Michaeli 一句話概括論文：作者用了一個稱之爲金字塔的網絡模型來對單張圖片操作，可以實現隨機生成類似圖片、提高分辨率、畫圖轉換爲圖片等功能。 （爲了方便你們看，
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相關文章
- 1. 論文筆記：SinGAN: Learning a Generative Model from a Single Natural Image
- 2. [論文筆記]：SinGAN: Learning a Generative Model from a Single Natural Image
- 3. SinGAN：Learning a Generative Model from a Single Natural Image
- 4. SinGAN: Learning a Generative Model from a Single Natural Image 閱讀筆記
- 5. SinGAN解讀: Learning a Generative Model from a Single Natural Image
- 6. [ICCV2019 Best Paper Award] SinGAN: Learning a Generative Model from a Single Natural Image
- 7. [ICCV2019] SinGAN: Learning a Generative Model from a Single Natural Image
- 8. SinGAN: Learning a Generative Model from a Single Natural Image（ICCV19）
- 9. 論文《Depth Estimation From a Light Field Image Pair With a Generative Model》學習
- 10. ICCV2019 最佳論文解讀：SinGAN