A Variational U-Net for Conditional Appearance and Shape Generation学习笔记
嘿嘿，各位看官，看了快一个月的ReID，今天给大家伙儿换换口味，欢迎新人GAN家族。。。。。 言归正传，深度生成网络在图片生成模型中有着很重要的作用。然而由于空间信息的丢失，往往都是通过图片来直接生成图片，而不是他们的固有的形状和外观。在这篇文章中作者使用了一个conditional unet网络进行形状指导下的图片生成，他的输出对外观进行自动编码。这个方法的优点是不需要同一个物体的不同照片而能够
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相关文章
- 1. A Variational U-Net for Conditional Appearance and Shape Generation
- 2. Latent Representation Learning For Artificial Bandwidth Extension Using A Conditional Variational Au...
- 3. Latent Representation Learning For Artificial Bandwidth Extension Using A Conditional Variational Au
- 4. UNet学习笔记
- 5. 论文笔记：A Novel Top-N Recommendation Approach Based on Conditional Variational Auto-Encoder
- 6. 李宏毅学习笔记31.GAN.02.Conditional Generation by GAN
- 7. Appearance-and-Relation Networks for Video Classification
- 8. Text Generation based Variational Autoencoders
- 9. 论文阅读：CTRL: A CONDITIONAL TRANSFORMER LANGUAGE MODEL FOR CONTROLLABLE GENERATION
- 10. 论文笔记--Appearance-and-Relation Networks for Video Classification