Hand Model

Hand modeling research focuses on creating accurate and realistic digital representations of human hands for applications in virtual and augmented reality, robotics, and computer vision. Current efforts concentrate on developing robust and efficient models, often employing neural networks (including diffusion models and graph convolutional networks) to capture intricate hand geometry, textures, and dynamics from various input modalities (e.g., images, videos, point clouds). These advancements are improving the realism and fidelity of digital hand avatars, enabling more natural human-computer interaction and facilitating progress in fields requiring precise hand pose estimation and manipulation.