VM-BHINet:Vision Mamba Bimanual Hand Interaction Network for 3D Interacting Hand Mesh Recovery From a Single RGB Image
Journal:
arXiv
Published Date:
Apr 20, 2025
Abstract
Understanding bimanual hand interactions is essential for realistic 3D pose
and shape reconstruction. However, existing methods struggle with occlusions,
ambiguous appearances, and computational inefficiencies. To address these
challenges, we propose Vision Mamba Bimanual Hand Interaction Network
(VM-BHINet), introducing state space models (SSMs) into hand reconstruction to
enhance interaction modeling while improving computational efficiency. The core
component, Vision Mamba Interaction Feature Extraction Block (VM-IFEBlock),
combines SSMs with local and global feature operations, enabling deep
understanding of hand interactions. Experiments on the InterHand2.6M dataset
show that VM-BHINet reduces Mean per-joint position error (MPJPE) and Mean
per-vertex position error (MPVPE) by 2-3%, significantly surpassing
state-of-the-art methods.
