Image segmentation is an essential task in computer vision that plays an important role in a variety of applications such as object recognition, autonomous driving, medical imaging, and others. It involves three segmentation tasks: semantic segmentation, which classifies individual pixels in an image into specific classes; instance segmentation, which detects and classifies each object instance in the image; and panoptic segmentation, which combines semantic and instance segmentation to identify and classify both pixels and object instances in the image. In recent decades, research has focused on designing specialized architectures for each of these fundamental tasks, and state-of-the-art results were achieved across different datasets and domains.