Human Segmentation

Human segmentation, the task of identifying and delineating human figures within images or videos, is a crucial area in computer vision with applications ranging from healthcare to e-commerce. Current research emphasizes improving accuracy and robustness, particularly in challenging scenarios like occlusions and limited data, often employing deep learning models such as U-Nets and variations of semantic segmentation networks, sometimes incorporating multi-task learning or novel approaches like temporal averaging for enhanced performance. These advancements are driving progress in applications such as 3D human pose estimation, personalized fashion recommendations, and assistive technologies for individuals with reading difficulties, while also addressing privacy concerns through techniques like ultrasound-based segmentation.