Prof. Syuhei Sato Profile

Prof. Syuhei Sato

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 2 May 2024 Paper

Sketch-guided flow field generation with diffusion model

Hengyuan Chang, Yichen Peng, Syuhei Sato, Haoran Xie

Proceedings Volume 13164, 131641G (2024) https://doi.org/10.1117/12.3018614

KEYWORDS: Design, Scene simulation, Fluid dynamics, Deep learning

Read Abstract +

The convergence of flow field generation with deep learning for augmenting the efficiency of flow simulation is a prominent pursuit. Current approaches primarily utilize conditional generative adversarial networks(cGANs) to generate velocity fields guided by sketches. In contrast, the cGAN training process exhibits instability. In this study, we propose a novel 2D velocity field design and generation framework that leverages the latent diffusion model (LDM). The sketch is a constraining condition that guides the denoising process within LDM and 2D velocity field reconstruction. Our framework is proficient in generating velocity fields that align with the shape of given sketches. We verified the robustness of the proposed framework in comparison to cGAN-based methods.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years