Segment Anything

Segment Anything (SAM) is a foundational model for image segmentation that aims to segment any object in an image given a simple prompt, such as a point or bounding box. Current research focuses on improving SAM's efficiency, accuracy, and adaptability to various domains and modalities (e.g., medical images, lidar data, video) through techniques like lightweight adapters, prompt refinement strategies, and multi-modal fusion. This versatile model has significant implications for numerous applications, including medical image analysis, autonomous driving, and remote sensing, by enabling efficient and accurate segmentation across diverse data types.