Cumincad : CUMINCAD Papers : Paper cdrf2019_208:embedGAN: A Method to Embed Images in GAN Latent Space

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
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last changed	2022/09/29 07:51