Instance Segmentation

Instance segmentation, a computer vision task, aims to identify and delineate individual objects within an image or point cloud, going beyond simple object detection by providing precise pixel-level masks. Current research emphasizes improving efficiency and accuracy, particularly in challenging scenarios like dense object arrangements, limited data, and noisy annotations; popular approaches involve transformer-based models, prototype-based methods, and techniques leveraging self-supervised learning or language-vision prompts. This field is crucial for diverse applications, including medical image analysis, autonomous driving, agricultural monitoring, and remote sensing, enabling automated analysis and improved decision-making in various domains.