Segment Anything Model

The Segment Anything Model (SAM) is a foundational model for image segmentation, aiming to provide a universal solution capable of segmenting any object in any image with minimal user input. Current research focuses on improving SAM's efficiency for resource-constrained environments, adapting it to specific domains like medical imaging and video, and exploring its use in conjunction with other models, such as large language models, for more complex tasks. SAM's strong zero-shot generalization capabilities and flexibility in prompt types are revolutionizing image segmentation, impacting fields ranging from medical diagnosis to autonomous driving through improved annotation efficiency and task performance.