mlsanityData to 14 Oct 2026

Multi-person 3D pose estimation from unlabelled data

arXiv 2212.08731 ↗First posted 16 Dec 2022cs.CV cs.AIcited by 2

Not on the map. Why?

Abstract (arXiv)

Its numerous applications make multi-human 3D pose estimation a remarkably impactful area of research. Nevertheless, assuming a multiple-view system composed of several regular RGB cameras, 3D multi-pose estimation presents several challenges. First of all, each person must be uniquely identified in the different views to separate the 2D information provided by the cameras. Secondly, the 3D pose estimation process from the multi-view 2D information of each person must be robust against noise and potential occlusions in the scenario. In this work, we address these two challenges with the help of deep learning. Specifically, we present a model based on Graph Neural Networks capable of predicting the cross-view correspondence of the people in the scenario along with a Multilayer Perceptron that takes the 2D points to yield the 3D poses of each person. These two models are trained in a self-supervised manner, thus avoiding the need for large datasets with 3D annotations.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 32 of its 57 references that are in the map. First posted on arXiv 16 Dec 2022.

Builds on

32 of 57 references.

References · 32

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  3. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
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  7. 2019PifPaf: Composite Fields for Human Pose Estimationcited by 120
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  11. 2018Learning Monocular 3D Human Pose Estimation from Multi-view Imagescited by 70
  12. 2019XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Cameracited by 68
20 more
  1. 2021OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Associationcited by 55
  2. 2021Conditional Directed Graph Convolution for 3D Human Pose Estimationcited by 52
  3. 2018Can 3D Pose be Learned from 2D Projections Alone?cited by 44
  4. 2020Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image Synthesiscited by 44
  5. 2022Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projectioncited by 39
  6. 2021Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereocited by 38
  7. 2021Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Imagescited by 38
  8. 2021Generalizable Human Pose Triangulationcited by 24
  9. 20222D Human Pose Estimation: A Surveycited by 21
  10. 2016RGB-D-based Action Recognition Datasets: A Surveycited by 14
  11. 2013Learning Human Pose Estimation Features with Convolutional Networkscited by 11
  12. 20173DOF Pedestrian Trajectory Prediction Learned from Long-Term Autonomous Mobile Robot Deployment Datacited by 11
  13. 2020Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimationcited by 10
  14. 2021Self-Supervised 3D Human Pose Estimation with Multiple-View Geometrycited by 10
  15. 2022Progressive Multi-view Human Mesh Recovery with Self-Supervisioncited by 9
  16. 2020Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimationcited by 5
  17. 2019Lifting 2d Human Pose to 3d : A Weakly Supervised Approachcited by 4
  18. 2022PoseGU: 3D Human Pose Estimation with Novel Human Pose Generator and Unbiased Learningcited by 4
  19. 2021Self-supervised Secondary Landmark Detection via 3D Representation Learningcited by 3
  20. 2020Multi-camera Torso Pose Estimation using Graph Neural Networkscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025C-DOG: Multi-View Multi-instance Feature Association Using Connected δ-Overlap Graphscited by 0
  2. 2026DisPOSE: Projected Polystochastic Diffusion for Self-Supervised Multi-View 3D Human Pose Estimationcited by 0