论文笔记：SinGAN: Learning a Generative Model from a Single Natural Image
论文笔记：SinGAN: Learning a Generative Model from a Single Natural Image 简介 这是ICCV2019 最佳论文。本文提出了一个多尺度的GAN，能够用单张图片进行训练，生成一系列高质量且类似的图片。这是博主第一次阅读GAN相关的文章，难免在理解上会出现一些问题，望见谅。 github代码：官方pytorch源码 这个算法可以用于图片生成
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- 1. [论文笔记]：SinGAN: Learning a Generative Model from a Single Natural Image
- 2. 2019-ICCV最佳论文-SinGAN: Learning a Generative Model from a Single Natural Image
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- 4. SinGAN：Learning a Generative Model from a Single Natural Image
- 5. SinGAN解读: Learning a Generative Model from a Single Natural Image
- 6. [ICCV2019 Best Paper Award] SinGAN: Learning a Generative Model from a Single Natural Image
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- 8. SinGAN: Learning a Generative Model from a Single Natural Image（ICCV19）
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相关文章
- 1. [论文笔记]：SinGAN: Learning a Generative Model from a Single Natural Image
- 2. 2019-ICCV最佳论文-SinGAN: Learning a Generative Model from a Single Natural Image
- 3. SinGAN: Learning a Generative Model from a Single Natural Image 阅读笔记
- 4. SinGAN：Learning a Generative Model from a Single Natural Image
- 5. SinGAN解读: 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. 论文《Depth Estimation From a Light Field Image Pair With a Generative Model》学习
- 10. 论文笔记_S2D.21_Deep Convolutional Neural Fields for Depth Estimation from a Single Image