Body Segmentation

Body segmentation, the task of partitioning an image into regions corresponding to different body parts, is crucial for numerous applications, ranging from medical image analysis to virtual try-ons in e-commerce. Current research emphasizes improving accuracy and efficiency, particularly focusing on robust handling of noisy data (e.g., occlusions, mislabeling) and leveraging hierarchical relationships between body parts through novel architectures like nnU-Net and transformer-based models. These advancements are driving progress in areas such as motion capture, medical diagnosis, and personalized experiences, improving both the precision of automated analyses and the speed of clinical workflows.