mlsanityData to 7 Oct 2026

HandFoldingNet: A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeleton

arXiv 2108.05545 ↗First posted 12 Aug 2021cs.CVcited by 16

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Abstract (arXiv)

With increasing applications of 3D hand pose estimation in various human-computer interaction applications, convolution neural networks (CNNs) based estimation models have been actively explored. However, the existing models require complex architectures or redundant computational resources to trade with the acceptable accuracy. To tackle this limitation, this paper proposes HandFoldingNet, an accurate and efficient hand pose estimator that regresses the hand joint locations from the normalized 3D hand point cloud input. The proposed model utilizes a folding-based decoder that folds a given 2D hand skeleton into the corresponding joint coordinates. For higher estimation accuracy, folding is guided by multi-scale features, which include both global and joint-wise local features. Experimental results show that the proposed model outperforms the existing methods on three hand pose benchmark datasets with the lowest model parameter requirement. Code is available at https://github.com/cwc1260/HandFold.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 21 of its 47 references that are in the map. First posted on arXiv 12 Aug 2021.

Builds on

21 of 47 references.

References · 21

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
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  9. 2015Capturing Hands in Action using Discriminative Salient Points and Physics Simulationcited by 115
  10. 2017V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Mapcited by 102
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9 more
  1. 2016Robust 3D Hand Pose Estimation in Single Depth Images: from Single-View CNN to Multi-View CNNscited by 29
  2. 2018Point-to-Pose Voting based Hand Pose Estimation using Residual Permutation Equivariant Layercited by 21
  3. 2015Hands Deep in Deep Learning for Hand Pose Estimationcited by 20
  4. 2020JGR-P2O: Joint Graph Reasoning based Pixel-to-Offset Prediction Network for 3D Hand Pose Estimation from a Single Depth Imagecited by 20
  5. 2017DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimationcited by 19
  6. 2017Dense 3D Regression for Hand Pose Estimationcited by 18
  7. 2017Pose Guided Structured Region Ensemble Network for Cascaded Hand Pose Estimationcited by 12
  8. 2016Model-based Deep Hand Pose Estimationcited by 11
  9. 2017Region Ensemble Network: Improving Convolutional Network for Hand Pose Estimationcited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 5; 2024: 4; 2025: 1; 2026: 3.

16 papers.

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  1. 2023An Outlook into the Future of Egocentric Visioncited by 84
  2. 2022Tracking and Reconstructing Hand Object Interactions from Point Cloud Sequences in the Wildcited by 17
  3. 2023A2J-Transformer: Anchor-to-Joint Transformer Network for 3D Interacting Hand Pose Estimation from a Single RGB Imagecited by 15
  4. 2024HandDiff: 3D Hand Pose Estimation with Diffusion on Image-Point Cloudcited by 12
  5. 2022TriHorn-Net: A Model for Accurate Depth-Based 3D Hand Pose Estimationcited by 7
  6. 2022Image-free Domain Generalization via CLIP for 3D Hand Pose Estimationcited by 4
  7. 2024ThermoHands: A Benchmark for 3D Hand Pose Estimation from Egocentric Thermal Imagescited by 4
  8. 2023OCHID-Fi: Occlusion-Robust Hand Pose Estimation in 3D via RF-Visioncited by 2
  9. 2025VM-BHINet:Vision Mamba Bimanual Hand Interaction Network for 3D Interacting Hand Mesh Recovery From a Single RGB Imagecited by 2
  10. 2023Pushing the Envelope for Depth-Based Semi-Supervised 3D Hand Pose Estimation with Consistency Trainingcited by 1
  11. 2023Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encodercited by 1
  12. 2024HandDAGT: A Denoising Adaptive Graph Transformer for 3D Hand Pose Estimationcited by 1
4 more
  1. 2024DOR3D-Net: Dense Ordinal Regression Network for 3D Hand Pose Estimationcited by 0
  2. 2026HandMCM: Multi-modal Point Cloud-based Correspondence State Space Model for 3D Hand Pose Estimationcited by 0
  3. 2026KPGrasp: Scalable Keypoint Flow Matching for Dexterous Grasp Generationcited by 0
  4. 2026KAD-Net: Kinematics-Aware Decoupled Learning for Robust 3D Hand Pose Estimation from a Single Depth Imagecited by 0