| Issue |
SHS Web of Conf.
Volume 174, 2023
2023 2nd International Conference on Science Education and Art Appreciation (SEAA 2023)
|
|
|---|---|---|
| Article Number | 02001 | |
| Number of page(s) | 4 | |
| Section | Digital Media Technology and Art Appreciation | |
| DOI | https://doi.org/10.1051/shsconf/202317402001 | |
| Published online | 11 August 2023 | |
Old Photos Restoration by Using VAE
1 Krieger School of Arts & Science, Johns Hopkins University, Baltimore, 21218, U.S.A
2 Shanghai Jianping High School, Shanghai, 200135, China
* Pma14@jh.edu
a 2814559307@qq.com
VAE is a generative model that “provides a probabilistic description of observations in potential Spaces”. Put simply, this means that VAE stores potential attributes as probability distributions. The idea of variational auto-encoders or VAE is deeply rooted in the methods of variational DB Bayesian and graphical models. This piece of work will discuss VAE Structure, VAE Loss Function, VAE Translation, and our final effects.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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