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SinGAN: Learning a Generative Model from a Single Natural Image(ICCV19)
時間 2020-12-30
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2. Method 學習的目標是an unconditional generative model that captures the internal statistics of a single training image x x x 不同於紋理生成(texture generation),本文針對的圖像都是general natural images 2.1. Multi-scale ar
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相關文章
1.
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 閱讀筆記
4.
SinGAN解讀: Learning a Generative Model from a Single Natural Image
5.
2019-ICCV最佳論文-SinGAN: Learning a Generative Model from a Single Natural Image
6.
[論文筆記]:SinGAN: Learning a Generative Model from a Single Natural Image
7.
[ICCV2019 Best Paper Award] SinGAN: Learning a Generative Model from a Single Natural Image
8.
[ICCV2019] SinGAN: Learning a Generative Model from a Single Natural Image
9.
論文《Depth Estimation From a Light Field Image Pair With a Generative Model》學習
10.
3D Face Reconstruction from a Single Image
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