# VM-BHINet:Vision Mamba Bimanual Hand Interaction Network for 3D Interacting Hand Mesh Recovery From a Single RGB Image

arXiv: https://arxiv.org/abs/2504.14618 · HTML: https://mlsanity.com/paper/2504.14618/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Placed in Video, motion and generative Mamba models, one of 10 directions in State-space sequence models (S4, Mamba).
- Builds on 29 of its 53 references that are in the map.
- First posted on arXiv 20 Apr 2025.

## Placed in

- State-space sequence models (S4, Mamba) / [Video, motion and generative Mamba models](https://mlsanity.com/ssm/video-motion-and-generative-mamba-models/)

## Builds on (most cited first, 29 of 29)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Mamba: Linear-Time Sequence Modeling with Selective State Spaces](https://mlsanity.com/paper/2312.00752/) (2023)
- [Efficiently Modeling Long Sequences with Structured State Spaces](https://mlsanity.com/paper/2111.00396/) (2021)
- [Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers](https://mlsanity.com/paper/2110.13985/) (2021)
- [H2O: Two Hands Manipulating Objects for First Person Interaction Recognition](https://mlsanity.com/paper/2104.11181/) (2021)
- [InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image](https://mlsanity.com/paper/2008.09309/) (2020)
- [Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimation](https://mlsanity.com/paper/2104.14639/) (2021)
- [Capturing Hands in Action using Discriminative Salient Points and Physics Simulation](https://mlsanity.com/paper/1506.02178/) (2015)
- [Interacting Attention Graph for Single Image Two-Hand Reconstruction](https://mlsanity.com/paper/2203.09364/) (2022)
- [Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera](https://mlsanity.com/paper/2106.08059/) (2021)
- [NeuralAnnot: Neural Annotator for 3D Human Mesh Training Sets](https://mlsanity.com/paper/2011.11232/) (2020)
- [Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction in A Triadic Interaction](https://mlsanity.com/paper/1906.04158/) (2019)
- [Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-pixel Part Segmentation](https://mlsanity.com/paper/2107.00434/) (2021)
- [ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction](https://mlsanity.com/paper/2303.05938/) (2023)
- [3D Interacting Hand Pose Estimation by Hand De-occlusion and Removal](https://mlsanity.com/paper/2207.11061/) (2022)
- [Body2Hands: Learning to Infer 3D Hands from Conversational Gesture Body Dynamics](https://mlsanity.com/paper/2007.12287/) (2020)
- [Two-hand Global 3D Pose Estimation Using Monocular RGB](https://mlsanity.com/paper/2006.01320/) (2020)
- [Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements](https://mlsanity.com/paper/2111.00763/) (2021)
- [RGB2Hands: Real-Time Tracking of 3D Hand Interactions from Monocular RGB Video](https://mlsanity.com/paper/2106.11725/) (2021)
- [HandFoldingNet: A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeleton](https://mlsanity.com/paper/2108.05545/) (2021)
- [A2J-Transformer: Anchor-to-Joint Transformer Network for 3D Interacting Hand Pose Estimation from a Single RGB Image](https://mlsanity.com/paper/2304.03635/) (2023)
- [Multi-modal Fusion Technology based on Vehicle Information: A Survey](https://mlsanity.com/paper/2211.06080/) (2022)
- [MMTL-UniAD: A Unified Framework for Multimodal and Multi-Task Learning in Assistive Driving Perception](https://mlsanity.com/paper/2504.02264/) (2025)
- [MeMaHand: Exploiting Mesh-Mano Interaction for Single Image Two-Hand Reconstruction](https://mlsanity.com/paper/2303.15718/) (2023)
- [Extract-and-Adaptation Network for 3D Interacting Hand Mesh Recovery](https://mlsanity.com/paper/2309.01943/) (2023)
- [LWA-HAND: Lightweight Attention Hand for Interacting Hand Reconstruction](https://mlsanity.com/paper/2208.09815/) (2022)
- [Path Planning for Air-Ground Robot Considering Modal Switching Point Optimization](https://mlsanity.com/paper/2305.08178/) (2023)
- [MIPD: A Multi-sensory Interactive Perception Dataset for Embodied Intelligent Driving](https://mlsanity.com/paper/2411.05881/) (2024)

## Built on by (most cited first, 2 of 2)

- [TEM^3-Learning: Time-Efficient Multimodal Multi-Task Learning for Advanced Assistive Driving](https://mlsanity.com/paper/2506.18084/) (2025)
- [CrossRay3D: Geometry and Distribution Guidance for Efficient Multimodal 3D Detection](https://mlsanity.com/paper/2510.15991/) (2025)

## Abstract (arXiv)

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.