mlsanityData to 7 Oct 2026

Hierarchical Graph Networks for 3D Human Pose Estimation

arXiv 2111.11927 ↗First posted 23 Nov 2021cs.CVcited by 11

Not on the map. Why?

Abstract (arXiv)

Recent 2D-to-3D human pose estimation works tend to utilize the graph structure formed by the topology of the human skeleton. However, we argue that this skeletal topology is too sparse to reflect the body structure and suffer from serious 2D-to-3D ambiguity problem. To overcome these weaknesses, we propose a novel graph convolution network architecture, Hierarchical Graph Networks (HGN). It is based on denser graph topology generated by our multi-scale graph structure building strategy, thus providing more delicate geometric information. The proposed architecture contains three sparse-to-fine representation subnetworks organized in parallel, in which multi-scale graph-structured features are processed and exchange information through a novel feature fusion strategy, leading to rich hierarchical representations. We also introduce a 3D coarse mesh constraint to further boost detail-related feature learning. Extensive experiments demonstrate that our HGN achieves the state-of-the art performance with reduced network parameters. Code is released at https://github.com/qingshi9974/BMVC2021-Hierarchical-Graph-Networks-for-3D-Human-Pose-Estimation.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 32 of its 44 references that are in the map. First posted on arXiv 23 Nov 2021.

Builds on

32 of 44 references.

References · 32

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  4. 2017Graph Attention Networkscited by 8,854
  5. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  6. 2017Inductive Representation Learning on Large Graphscited by 6,284
  7. 2017Non-local Neural Networkscited by 2,290
  8. 2016Convolutional Neural Networks on Graphs with Fast Localized Spectral Filteringcited by 2,085
  9. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  10. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,199
  11. 2013Spectral Networks and Locally Connected Networks on Graphscited by 1,097
  12. 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 692
20 more
  1. 2016Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervisioncited by 493
  2. 2019Graph U-Netscited by 489
  3. 2017A simple yet effective baseline for 3d human pose estimationcited by 401
  4. 20183D human pose estimation in video with temporal convolutions and semi-supervised trainingcited by 401
  5. 2017Cascaded Pyramid Network for Multi-Person Pose Estimationcited by 341
  6. 2016Learning Convolutional Neural Networks for Graphscited by 314
  7. 2017Integral Human Pose Regressioncited by 255
  8. 2020Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Posecited by 248
  9. 2019Semantic Graph Convolutional Networks for 3D Human Pose Regressioncited by 204
  10. 2019Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Imagecited by 131
  11. 2017Compositional Human Pose Regressioncited by 124
  12. 2017Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approachcited by 114
  13. 2018Ordinal Depth Supervision for 3D Human Pose Estimationcited by 107
  14. 2021Graph Stacked Hourglass Networks for 3D Human Pose Estimationcited by 94
  15. 20183D Human Pose Estimation in the Wild by Adversarial Learningcited by 86
  16. 2021Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimationcited by 62
  17. 2019HEMlets Pose: Learning Part-Centric Heatmap Triplets for Accurate 3D Human Pose Estimationcited by 50
  18. 2018OriNet: A Fully Convolutional Network for 3D Human Pose Estimationcited by 28
  19. 2020HDNet: Human Depth Estimation for Multi-Person Camera-Space Localizationcited by 20
  20. 2020SIA-GCN: A Spatial Information Aware Graph Neural Network with 2D Convolutions for Hand Pose Estimationcited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 3; 2024: 2; 2025: 2; 2026: 3.

11 papers.

  1. 2023Cascade-Zero123: One Image to Highly Consistent 3D with Self-Prompted Nearby Viewscited by 32
  2. 2024Image Compression for Machine and Human Vision with Spatial-Frequency Adaptationcited by 26
  3. 2023Pose-Oriented Transformer with Uncertainty-Guided Refinement for 2D-to-3D Human Pose Estimationcited by 19
  4. 2023ActionPrompt: Action-Guided 3D Human Pose Estimation With Text and Pose Promptingcited by 8
  5. 2025HiPART: Hierarchical Pose AutoRegressive Transformer for Occluded 3D Human Pose Estimationcited by 8
  6. 2024BEM: Balanced and Entropy-based Mix for Long-Tailed Semi-Supervised Learningcited by 6
  7. 2026MuPPet: Multi-person 2D-to-3D Pose Liftingcited by 2
  8. 2026CIGPose: Causal Intervention Graph Neural Network for Whole-Body Pose Estimationcited by 1
  9. 2022K-Order Graph-oriented Transformer with GraAttention for 3D Pose and Shape Estimationcited by 0
  10. 2025HyperDiff: Hypergraph Guided Diffusion Model for 3D Human Pose Estimationcited by 0
  11. 2026MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse Observationscited by 0