tfzhou/ProtoSeg
CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View
This project offers an improved way to automatically identify and label different objects or regions within images, a process known as semantic segmentation. It takes an image as input and outputs a pixel-level map where each pixel is assigned to a specific category (e.g., road, building, person). This is useful for computer vision researchers and engineers who build systems that need to understand scenes precisely.
388 stars. No commits in the last 6 months.
Use this if you are working on advanced computer vision applications requiring precise image segmentation and want to explore a robust, nonparametric approach.
Not ideal if you are looking for a simple, out-of-the-box solution without diving into the underlying segmentation model design.
Stars
388
Forks
43
Language
Python
License
MIT
Category
Last pushed
Jun 30, 2022
Commits (30d)
0
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