mlsanityData to 7 Oct 2026

Hands Deep in Deep Learning for Hand Pose Estimation

arXiv 1502.06807 ↗First posted 24 Feb 2015cs.CVcited by 20

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Abstract (arXiv)

We introduce and evaluate several architectures for Convolutional Neural Networks to predict the 3D joint locations of a hand given a depth map. We first show that a prior on the 3D pose can be easily introduced and significantly improves the accuracy and reliability of the predictions. We also show how to use context efficiently to deal with ambiguities between fingers. These two contributions allow us to significantly outperform the state-of-the-art on several challenging benchmarks, both in terms of accuracy and computation times.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Feb 2015.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 7; 2023: 3; 2024: 2; 2025: 0; 2026: 3.

20 papers.

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  1. 2021Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-pixel Part Segmentationcited by 40
  2. 2021Multi-Anchor Active Domain Adaptation for Semantic Segmentationcited by 29
  3. 2022Tracking and Reconstructing Hand Object Interactions from Point Cloud Sequences in the Wildcited by 17
  4. 2021HandFoldingNet: A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeletoncited by 16
  5. 2022Attention guided global enhancement and local refinement network for semantic segmentationcited by 10
  6. 2022TriHorn-Net: A Model for Accurate Depth-Based 3D Hand Pose Estimationcited by 7
  7. 2021Boundary Guided Context Aggregation for Semantic Segmentationcited by 5
  8. 2022A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasetscited by 5
  9. 2023MADAv2: Advanced Multi-Anchor Based Active Domain Adaptation Segmentationcited by 5
  10. 2022Generalized Product-of-Experts for Learning Multimodal Representations in Noisy Environmentscited by 4
  11. 2024Single-View Scene Point Cloud Human Grasp Generationcited by 4
  12. 2022Modern Augmented Reality: Applications, Trends, and Future Directionscited by 3
8 more
  1. 2022Analysis of the performance of U-Net neural networks for the segmentation of living cellscited by 2
  2. 2026Cardiac fat segmentation using computed tomography and an image-to-image conditional generative adversarial neural networkcited by 2
  3. 2021HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimationcited by 1
  4. 2023Pushing the Envelope for Depth-Based Semi-Supervised 3D Hand Pose Estimation with Consistency Trainingcited by 1
  5. 2023JetSeg: Efficient Real-Time Semantic Segmentation Model for Low-Power GPU-Embedded Systemscited by 1
  6. 2024Augmented Efficiency: Reducing Memory Footprint and Accelerating Inference for 3D Semantic Segmentation through Hybrid Visioncited by 1
  7. 2026GeoHand: Unlocking Prior Geometry Knowledge for Monocular 3D Hand Reconstructioncited by 1
  8. 2026Touchless Intraoperative Image Access System Based on Vision-Based Hand Trackingcited by 0