Large Language Models (LLMs) for Image Segmentation: A Comprehensive Review

Image segmentation, a critical task in computer vision, involves dividing an image into meaningful segments, often leading to significant advancements in areas like medical imaging, autonomous driving, and object detection. Traditionally, convolutional neural networks (CNNs) have dominated this field. However, recent advancements in large language models (LLMs) have opened new avenues for image segmentation tasks. This review paper aims to provide an extensive overview of the application of LLMs in image segmentation, discussing their architectures, methodologies, advantages, limitations, and future directions.