Body Part Segmentation

Body part segmentation, the task of identifying and delineating individual body parts within an image or video, is a crucial area of computer vision research aimed at improving the accuracy and efficiency of human-centric applications. Current research emphasizes developing robust models, often leveraging deep neural networks like transformers, that can handle variations in pose, viewpoint, occlusion, and domain shifts, often incorporating pose estimation information to improve segmentation accuracy. These advancements are driving progress in diverse fields, including human-computer interaction, healthcare (e.g., infant movement assessment and medical research), and behavioral analysis of animals, by enabling more sophisticated and accurate analysis of human and animal movement and behavior.