Image Segmentation

Image segmentation, the process of partitioning an image into meaningful regions, aims to accurately delineate objects or areas of interest within a visual scene. Current research heavily emphasizes leveraging foundation models like Segment Anything Model (SAM) and its variants, often incorporating adaptations such as dual-branch architectures or efficient adapters to improve performance on specific domains (e.g., medical imaging, remote sensing) and address limitations like memory consumption. These advancements are significantly impacting diverse fields, from medical diagnosis and industrial inspection to autonomous driving and cultural heritage preservation, by enabling more accurate, efficient, and automated image analysis.