mlsanityData to 14 Oct 2026

Efficient Virtual View Selection for 3D Hand Pose Estimation

arXiv 2203.15458 ↗First posted 29 Mar 2022cs.CVcited by 6

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Abstract (arXiv)

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. In this paper, we propose a new virtual view selection and fusion module for 3D hand pose estimation from single depth.We propose to automatically select multiple virtual viewpoints for pose estimation and fuse the results of all and find this empirically delivers accurate and robust pose estimation. In order to select most effective virtual views for pose fusion, we evaluate the virtual views based on the confidence of virtual views using a light-weight network via network distillation. Experiments on three main benchmark datasets including NYU, ICVL and Hands2019 demonstrate that our method outperforms the state-of-the-arts on NYU and ICVL, and achieves very competitive performance on Hands2019-Task1, and our proposed virtual view selection and fusion module is both effective for 3D hand pose estimation.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 14 of its 24 references that are in the map. First posted on arXiv 29 Mar 2022.

Builds on

14 of 24 references.

References · 14

  1. 2017Attention Is All You Needcited by 60,361
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  3. 2015Spatial Transformer Networkscited by 1,429
  4. 2017V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Mapcited by 102
  5. 2019A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Imagecited by 56
  6. 2020Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Imagescited by 37
  7. 2016Robust 3D Hand Pose Estimation in Single Depth Images: from Single-View CNN to Multi-View CNNscited by 29
  8. 2020Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interactioncited by 24
  9. 2017Dense 3D Regression for Hand Pose Estimationcited by 18
  10. 2020AWR: Adaptive Weighting Regression for 3D Hand Pose Estimationcited by 17
  11. 2017Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Imagescited by 15
  12. 2016Spatial Attention Deep Net with Partial PSO for Hierarchical Hybrid Hand Pose Estimationcited by 8
2 more
  1. 2020Deep Reinforcement Learning for Active Human Pose Estimationcited by 7
  2. 2020HandAugment: A Simple Data Augmentation Method for Depth-Based 3D Hand Pose Estimationcited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 3; 2023: 1; 2024: 1; 2025: 0; 2026: 1.

6 papers.

  1. 20223D Vision with Transformers: A Surveycited by 21
  2. 2022Tracking and Reconstructing Hand Object Interactions from Point Cloud Sequences in the Wildcited by 17
  3. 2024HandDiff: 3D Hand Pose Estimation with Diffusion on Image-Point Cloudcited by 12
  4. 2022Image-free Domain Generalization via CLIP for 3D Hand Pose Estimationcited by 4
  5. 2023Towards Ubiquitous Intelligent Hand Interactioncited by 0
  6. 2026KAD-Net: Kinematics-Aware Decoupled Learning for Robust 3D Hand Pose Estimation from a Single Depth Imagecited by 0