3D Hand Pose Estimation
64 papers with code • 5 benchmarks • 16 datasets
Image: Zimmerman et l
Benchmarks
These leaderboards are used to track progress in 3D Hand Pose Estimation
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Libraries
Use these libraries to find 3D Hand Pose Estimation models and implementationsDatasets
FreiHAND
HO-3D
DexYCB
AGORA
InterHand2.6M
ExPose
3D Hand Pose
First-Person Hand Action Benchmark
EgoDexter
SynthHands
Latest papers
HandR2N2: Iterative 3D Hand Pose Estimation Using a Residual Recurrent Neural Network
cwc1260/handr2n2
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ICCV 2023
3D hand pose estimation is a critical task in various human-computer interaction applications.
H3WB: Human3.6M 3D WholeBody Dataset and Benchmark
wholebody3d/wholebody3d
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ICCV 2023
We also propose three tasks: i) 3D whole-body pose lifting from 2D complete whole-body pose, ii) 3D whole-body pose lifting from 2D incomplete whole-body pose, and iii) 3D whole-body pose estimation from a single RGB image.
Interacting Hand-Object Pose Estimation via Dense Mutual Attention
rongakowang/densemutualattention
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In contrast, we propose a novel dense mutual attention mechanism that is able to model fine-grained dependencies between the hand and the object.
Hierarchical Temporal Transformer for 3D Hand Pose Estimation and Action Recognition from Egocentric RGB Videos
fylwen/htt
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CVPR 2023
Understanding dynamic hand motions and actions from egocentric RGB videos is a fundamental yet challenging task due to self-occlusion and ambiguity.
Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformers
Transformer encoder architectures have recently achieved state-of-the-art results on monocular 3D human mesh reconstruction, but they require a substantial number of parameters and expensive computations.
TriHorn-Net: A Model for Accurate Depth-Based 3D Hand Pose Estimation
The second innovation is PixDropout, which is, to the best of our knowledge, the first appearance-based data augmentation method for hand depth images.
Efficient Virtual View Selection for 3D Hand Pose Estimation
iscas3dv/handpose-virtualview
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3D hand pose estimation from single depth is a fundamental problem in computer vision, and has wide applications. However, the existing methods still can not achieve satisfactory hand pose estimation results due to view variation and occlusion of human hand.
Mining Multi-View Information: A Strong Self-Supervised Framework for Depth-Based 3D Hand Pose and Mesh Estimation
However, these methods ignore the rich semantic information in each view and ignore the complex dependencies between different regions of different views.
Local and Global Point Cloud Reconstruction for 3D Hand Pose Estimation
shichengchen/multiviewdataset
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This paper addresses the 3D point cloud reconstruction and 3D pose estimation of the human hand from a single RGB image.
MobRecon: Mobile-Friendly Hand Mesh Reconstruction from Monocular Image
SeanChenxy/HandMesh
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CVPR 2022
In this work, we propose a framework for single-view hand mesh reconstruction, which can simultaneously achieve high reconstruction accuracy, fast inference speed, and temporal coherence.
