OpenGVLab/DDPS
Official Implementation of "Denoising Diffusion Semantic Segmentation with Mask Prior Modeling"
This project improves the accuracy of semantic segmentation, which is the task of labeling every pixel in an image with a category like 'road', 'building', or 'person'. It takes an image as input and outputs a more precise segmentation mask. Computer vision engineers, researchers, and practitioners working on image analysis applications would find this useful.
No commits in the last 6 months.
Use this if you need to achieve highly accurate and detailed image segmentation for tasks like autonomous driving, medical imaging, or satellite imagery analysis.
Not ideal if you are looking for a simple, out-of-the-box solution without diving into model configurations or if raw speed is your absolute top priority over precision.
Stars
73
Forks
4
Language
Python
License
—
Category
Last pushed
Jul 27, 2023
Commits (30d)
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