# Interacting Hand-Object Pose Estimation via Dense Mutual Attention

arXiv: https://arxiv.org/abs/2211.08805 · HTML: https://mlsanity.com/paper/2211.08805/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- Builds on 41 of its 52 references that are in the map.
- First posted on arXiv 16 Nov 2022.

## Builds on (most cited first, 30 of 41)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [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)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [ImageNet Large Scale Visual Recognition Challenge](https://mlsanity.com/paper/1409.0575/) (2014)
- [How Powerful are Graph Neural Networks?](https://mlsanity.com/paper/1810.00826/) (2018)
- [Accelerating 3D Deep Learning with PyTorch3D](https://mlsanity.com/paper/2007.08501/) (2020)
- [PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes](https://mlsanity.com/paper/1711.00199/) (2017)
- [Neural 3D Mesh Renderer](https://mlsanity.com/paper/1711.07566/) (2017)
- [GRAB: A Dataset of Whole-Body Human Grasping of Objects](https://mlsanity.com/paper/2008.11200/) (2020)
- [PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation](https://mlsanity.com/paper/1812.11788/) (2018)
- [Learning joint reconstruction of hands and manipulated objects](https://mlsanity.com/paper/1904.05767/) (2019)
- [PARE: Part Attention Regressor for 3D Human Body Estimation](https://mlsanity.com/paper/2104.08527/) (2021)
- [DexYCB: A Benchmark for Capturing Hand Grasping of Objects](https://mlsanity.com/paper/2104.04631/) (2021)
- [DeepIM: Deep Iterative Matching for 6D Pose Estimation](https://mlsanity.com/paper/1804.00175/) (2018)
- [I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image](https://mlsanity.com/paper/2008.03713/) (2020)
- [FreiHAND: A Dataset for Markerless Capture of Hand Pose and Shape from Single RGB Images](https://mlsanity.com/paper/1909.04349/) (2019)
- [Learning to Estimate 3D Hand Pose from Single RGB Images](https://mlsanity.com/paper/1705.01389/) (2017)
- [ContactPose: A Dataset of Grasps with Object Contact and Hand Pose](https://mlsanity.com/paper/2007.09545/) (2020)
- [Embodied Hands: Modeling and Capturing Hands and Bodies Together](https://mlsanity.com/paper/2201.02610/) (2022)
- [Grasping Field: Learning Implicit Representations for Human Grasps](https://mlsanity.com/paper/2008.04451/) (2020)
- [3D Hand Shape and Pose Estimation from a Single RGB Image](https://mlsanity.com/paper/1903.00812/) (2019)
- [GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimator](https://mlsanity.com/paper/2102.12145/) (2021)
- [Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild](https://mlsanity.com/paper/2004.01946/) (2020)
- [Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time](https://mlsanity.com/paper/2106.05266/) (2021)
- [Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstruction](https://mlsanity.com/paper/2004.13449/) (2020)
- [CPF: Learning a Contact Potential Field to Model the Hand-Object Interaction](https://mlsanity.com/paper/2012.00924/) (2020)
- [Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimation](https://mlsanity.com/paper/2104.14639/) (2021)
- [HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation](https://mlsanity.com/paper/2004.00060/) (2020)

## Built on by (most cited first, 22 of 22)

- [HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields](https://mlsanity.com/paper/2402.17062/) (2024)
- [Get a Grip: Reconstructing Hand-Object Stable Grasps in Egocentric Videos](https://mlsanity.com/paper/2312.15719/) (2023)
- [DeepSimHO: Stable Pose Estimation for Hand-Object Interaction via Physics Simulation](https://mlsanity.com/paper/2310.07206/) (2023)
- [DiffHand: End-to-End Hand Mesh Reconstruction via Diffusion Models](https://mlsanity.com/paper/2305.13705/) (2023)
- [UniHOPE: A Unified Approach for Hand-Only and Hand-Object Pose Estimation](https://mlsanity.com/paper/2503.13303/) (2025)
- [Sparse multi-view hand-object reconstruction for unseen environments](https://mlsanity.com/paper/2405.01353/) (2024)
- [QORT-Former: Query-optimized Real-time Transformer for Understanding Two Hands Manipulating Objects](https://mlsanity.com/paper/2502.19769/) (2025)
- [Occlusion-Aware 3D Hand-Object Pose Estimation with Masked AutoEncoders](https://mlsanity.com/paper/2506.10816/) (2025)
- [Reconstructing Objects along Hand Interaction Timelines in Egocentric Video](https://mlsanity.com/paper/2512.07394/) (2025)
- [V-Hands: Touchscreen-based Hand Tracking for Remote Whiteboard Interaction](https://mlsanity.com/paper/2409.13347/) (2024)
- [Hand-object reconstruction via interaction-aware graph attention mechanism](https://mlsanity.com/paper/2409.17629/) (2024)
- [Kinematics-based 3D Human-Object Interaction Reconstruction from Single View](https://mlsanity.com/paper/2407.14043/) (2024)
- [A Versatile and Differentiable Hand-Object Interaction Representation](https://mlsanity.com/paper/2409.16855/) (2024)
- [Human Motion Prediction, Reconstruction, and Generation](https://mlsanity.com/paper/2502.15956/) (2025)
- [Visuo-Acoustic Hand Pose and Contact Estimation](https://mlsanity.com/paper/2508.00852/) (2025)
- [EgoLoc: A Generalizable Solution for Temporal Interaction Localization in Egocentric Videos](https://mlsanity.com/paper/2508.12349/) (2025)
- [GenHOI: Generalized Hand-Object Pose Estimation with Occlusion Awareness](https://mlsanity.com/paper/2603.19013/) (2026)
- [HandS3C: 3D Hand Mesh Reconstruction with State Space Spatial Channel Attention from RGB images](https://mlsanity.com/paper/2405.01066/) (2024)
- [6D Pose Estimation on Spoons and Hands](https://mlsanity.com/paper/2505.02335/) (2025)
- [VPHO: Joint Visual-Physical Cue Learning and Aggregation for Hand-Object Pose Estimation](https://mlsanity.com/paper/2511.12030/) (2025)
- [Learning High-Fidelity Cloth Animation via Skinning-Free Image Transfer](https://mlsanity.com/paper/2512.05593/) (2025)
- [Privacy-Preserving Full-Body Meshing from mmWave Radar via Mesh Foundation Model Supervision](https://mlsanity.com/paper/2609.34768/) (2026)

## Abstract (arXiv)

3D hand-object pose estimation is the key to the success of many computer vision applications. The main focus of this task is to effectively model the interaction between the hand and an object. To this end, existing works either rely on interaction constraints in a computationally-expensive iterative optimization, or consider only a sparse correlation between sampled hand and object keypoints. In contrast, we propose a novel dense mutual attention mechanism that is able to model fine-grained dependencies between the hand and the object. Specifically, we first construct the hand and object graphs according to their mesh structures. For each hand node, we aggregate features from every object node by the learned attention and vice versa for each object node. Thanks to such dense mutual attention, our method is able to produce physically plausible poses with high quality and real-time inference speed. Extensive quantitative and qualitative experiments on large benchmark datasets show that our method outperforms state-of-the-art methods. The code is available at https://github.com/rongakowang/DenseMutualAttention.git.