From Pixels to Masks: Understanding Mask2Former Step by Step
A step-by-step guide to the Mask2Former architecture and code — explained with intuition, visuals, and pseudo-code.
Types of Segmentation:
- Semantic Segmentation: Every pixel is labeled with a class, not an instance.
The model does not differentiate between different cars or different people. It just knows what pixel belong to which category. - Instance Segmentation: Now we care about all instances of the same class. But it does not include the background classes.
In this case, Person 1 and Person 2 will be marked separately, so will Car 1 and Car 2. - Panoptic Segmentation: Best of both worlds.
It combines:
- Stuff (background, texture-like areas → road, sky, grass)
- Things (distinct countable objects → cars, people, trees)
Every pixel in the image is assigned both a semantic class and an instance ID.
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