Part Segmentation

Part segmentation, the task of dividing an object into its constituent parts, is a crucial area of computer vision research aiming to improve object understanding and manipulation. Current research focuses on developing robust and generalizable methods, often employing transformer-based architectures and leveraging large pre-trained models like Segment Anything Model (SAM) to address challenges such as limited annotated data and diverse object morphologies. These advancements are significant for various applications, including robotics (grasping, manipulation), medical imaging (disease detection, surgical assistance), and 3D modeling (reconstruction, animation), where accurate part identification is essential for effective task completion.