Artificial Intelligence Computer Science Mathematics
STEM, Research, The University of Hong Kong

Research Report - Utilising Stable Diffusion for Image Semantic Matching

Go to the profile of (Marco) Cheng Yu Ting
(Marco) Cheng Yu Ting
Student, The University of Hong Kong
Like
Go to the profile of Tevin Yeung Man Tak

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

Share with...

This is a representation of how your post may appear on social media. The actual post will vary between social networks

Preview

Open

The research aims to improve the accuracy of point-wise image semantic matching, especially with a small margin of error, by utilising multiple latent layers within the Stable Diffusion model.

Go to the profile of (Marco) Cheng Yu Ting
(Marco) Cheng Yu Ting (He/Him)
Student, The University of Hong Kong

Recommended Content

Cookie Settings

We and selected partners, use cookies or similar technologies as specified in the cookie policy and privacy policy.

You can consent to the use of such technologies by closing this notice.

Cookie Control

Customise your preferences for any tracking technology

The following allows you to customize your consent preferences for any tracking technology used to help us achieve the features and activities described below. To learn more about how these trackers help us and how they work, refer to the cookie policy. You may review and change your preferences at any time.

Cookie policy Privacy policy
Always active, cannot be turned off
More information

These trackers are used for activities that are strictly necessary to operate or deliver the service you requested from us and, therefore, do not require you to consent.

More information

These trackers help us to deliver personalized marketing content and to operate, serve and track ads.

More information

These trackers help us to deliver personalized marketing content to you based on your behaviour and to operate, serve and track social advertising.

More information

These trackers help us to measure traffic and analyze your behaviour with the goal of improving our service.

More information

These trackers help us to provide a personalized user experience by improving the quality of your preference management options, and by enabling the interaction with external networks and platforms.