(22)[NIPS16] PixelCNN：Conditional Image Generation with PixelCNN Decoders
计划完成深度学习入门的126篇论文第二十一篇，DeepMind的Alex Graves等领导研究一种新的生成Image模型。 ABSTRACT&INTRODUCTION 摘要 本工做探索了基于PixelCNN结构的条件图像生成新图像密度模型。该模型能够以任何向量为条件，包括描述性标签或标记，或由其余网络建立的潜在嵌入。当以ImageNet数据库中的类标签为条件时，该模型可以生成表明不一样动物、对象
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相关文章
- 1. 《Conditional Image Generation with PixelCNN Decoders》之Pixcel CNN---gated Pixcel CNN 阅读笔记
- 2. 如何比较PixelCNN与DCGAN两种Image generation方法？
- 3. Pose Guided Person Image Generation
- 4. 论文阅读：Neural Image Caption Generation with Visual Attention
- 5. AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
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- 9. Automatic Trimap Generation for Image Matting
- 10. CVAE-GAN：Fine-Grained Image Generation through Asymmetric Training