Context Segmentation

Context segmentation aims to identify and delineate objects within an image based on surrounding contextual information, reducing reliance on extensive labeled datasets. Current research focuses on leveraging large vision models and transformer architectures, often incorporating in-context learning paradigms and novel prompt selection strategies to improve accuracy and efficiency across diverse tasks, including medical image analysis and object segmentation in complex scenes. This field is significant for advancing artificial intelligence capabilities in image understanding and has practical implications for various applications, such as medical diagnosis, autonomous driving, and remote sensing.