High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs个人理解
看了这篇论文 觉得有趣的地方 希望能为后者提供些不同看法，不足之处希望各位指正 一、 该论文通过改进提高了生成图像的像素，有趣的一点在于作者能通过low-dimension feature channel 作为生成器的输入来实现实例级的目标修改，效果如下图： 论文中该方法的实现， 1）作者训练一个生成器网络E去找图片中每个实例对应的低维特征，E是一个encoder-decoder标准结构网络。 2
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相关文章
- 1. 论文阅读High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
- 2. 《High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs》论文笔记
- 3. Semantic Image Synthesis with Spatially-Adaptive Normalization（CVPR19）
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- 7. (Pixel2PixelGANs)Image-to-Image translation with conditional adversarial networks
- 8. LinkNet with Pretrained Encoder and Dilated Convolution for HighResolution Satellite Image
- 9. Generative Adversarial Text to Image Synthesis
- 10. Image Captioning with Semantic Attention