| id |
cdrf2019_208 |
| authors |
Zhijia Chen, Weixin Huang, and Ziniu Luo |
| year |
2020 |
| title |
embedGAN: A Method to Embed Images in GAN Latent Space |
| doi |
https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_20
|
| source |
Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020) |
| summary |
GAN is an efficient generative model. By performing a latent walk in GAN, the generation result can be adjusted. However, the latent walk cannot start from a selected image. The embedGAN is proposed to embed selected images into GAN and remain the generation effect. It contains an embedded network and a generative network. Application cases of residential interior design are given in the article. With advantages of a low computing cost and short training time, embedGAN shows its potential. The embedGAN algorithm framework can be applied to various GANs. |
| series |
cdrf |
| email |
|
| full text |
 file.pdf (2,336,231 bytes) |
| references |
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