Human Silhouette

Human silhouette analysis focuses on extracting meaningful information from the outline of a human figure, primarily for applications like gait recognition, 3D body reconstruction, and virtual try-on. Current research emphasizes developing robust methods for silhouette extraction and analysis, even under challenging conditions like occlusions and varying viewpoints, often employing diffusion models, neural networks (including convolutional and graph convolutional networks), and multi-modal approaches that integrate silhouette data with other information such as skeletons or RGB images. These advancements improve the accuracy and reliability of human-centric computer vision tasks, impacting fields ranging from biometrics and human-computer interaction to fashion technology and robotics.