mlsanityData to 14 Oct 2026

PoseGU: 3D Human Pose Estimation with Novel Human Pose Generator and Unbiased Learning

arXiv 2207.03618 ↗First posted 7 Jul 2022cs.CV cs.LGcited by 4

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Abstract (arXiv)

3D pose estimation has recently gained substantial interests in computer vision domain. Existing 3D pose estimation methods have a strong reliance on large size well-annotated 3D pose datasets, and they suffer poor model generalization on unseen poses due to limited diversity of 3D poses in training sets. In this work, we propose PoseGU, a novel human pose generator that generates diverse poses with access only to a small size of seed samples, while equipping the Counterfactual Risk Minimization to pursue an unbiased evaluation objective. Extensive experiments demonstrate PoseGU outforms almost all the state-of-the-art 3D human pose methods under consideration over three popular benchmark datasets. Empirical analysis also proves PoseGU generates 3D poses with improved data diversity and better generalization ability.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 27 of its 45 references that are in the map. First posted on arXiv 7 Jul 2022.

Builds on

27 of 45 references.

References · 27

  1. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  2. 2017End-to-end Recovery of Human Shape and Posecited by 885
  3. 20183D human pose estimation in video with temporal convolutions and semi-supervised trainingcited by 403
  4. 2017A simple yet effective baseline for 3d human pose estimationcited by 401
  5. 2020Unbiased Scene Graph Generation from Biased Trainingcited by 356
  6. 2019Semantic Graph Convolutional Networks for 3D Human Pose Regressioncited by 204
  7. 2017Single-Shot Multi-Person 3D Pose Estimation From Monocular RGBcited by 195
  8. 2019Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Imagecited by 132
  9. 2017VNect: Real-time 3D Human Pose Estimation with a Single RGB Cameracited by 129
  10. 2017Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approachcited by 115
  11. 2021Counterfactual Generative Networkscited by 111
  12. 2019Unsupervised 3D Pose Estimation with Geometric Self-Supervisioncited by 95
15 more
  1. 2019Single-Stage Multi-Person Pose Machinescited by 95
  2. 2020SRNet: Improving Generalization in 3D Human Pose Estimation with a Split-and-Recombine Approachcited by 94
  3. 2021PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimationcited by 89
  4. 20183D Human Pose Estimation in the Wild by Adversarial Learningcited by 86
  5. 2019RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimationcited by 85
  6. 2020Cascaded deep monocular 3D human pose estimation with evolutionary training datacited by 80
  7. 2019Monocular 3D Human Pose Estimation by Generation and Ordinal Rankingcited by 76
  8. 2019Counterfactual Risk Assessments, Evaluation, and Fairnesscited by 59
  9. 2016Synthesizing Training Images for Boosting Human 3D Pose Estimationcited by 52
  10. 2016MoCap-guided Data Augmentation for 3D Pose Estimation in the Wildcited by 37
  11. 2020Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimationcited by 36
  12. 2015Counterfactual Risk Minimization: Learning from Logged Bandit Feedbackcited by 33
  13. 2018OriNet: A Fully Convolutional Network for 3D Human Pose Estimationcited by 28
  14. 2018A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Imagescited by 19
  15. 2020Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimationcited by 10

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Cited by year (2026 to 14 Oct)

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

4 papers.

  1. 2022Multi-person 3D pose estimation from unlabelled datacited by 2
  2. 2024Data Augmentation in Human-Centric Visioncited by 2
  3. 2025AugLift: Depth-Aware Input Reparameterization Improves Domain Generalization in 2D-to-3D Pose Liftingcited by 1
  4. 2026Enhancing Domain Generalization in 3D Human Pose Estimation through Controllable Generative Augmentationcited by 0