Hand Mesh

Hand mesh reconstruction aims to create accurate 3D models of hands from images or video, crucial for applications like virtual reality and human-computer interaction. Current research focuses on improving the accuracy and efficiency of reconstruction, employing various deep learning architectures such as transformers, graph convolutional networks, and diffusion models, often incorporating multi-view data or leveraging inverse rendering techniques to refine mesh geometry and texture. These advancements are driving progress in realistic hand avatars, intuitive interfaces, and improved understanding of hand-object interactions, impacting fields ranging from gaming to robotics.