mlsanityData to 7 Oct 2026

View Consistency Aware Holistic Triangulation for 3D Human Pose Estimation

arXiv 2302.11301 ↗First posted 22 Feb 2023cs.CVcited by 6

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Abstract (arXiv)

The rapid development of multi-view 3D human pose estimation (HPE) is attributed to the maturation of monocular 2D HPE and the geometry of 3D reconstruction. However, 2D detection outliers in occluded views due to neglect of view consistency, and 3D implausible poses due to lack of pose coherence, remain challenges. To solve this, we introduce a Multi-View Fusion module to refine 2D results by establishing view correlations. Then, Holistic Triangulation is proposed to infer the whole pose as an entirety, and anatomy prior is injected to maintain the pose coherence and improve the plausibility. Anatomy prior is extracted by PCA whose input is skeletal structure features, which can factor out global context and joint-by-joint relationship from abstract to concrete. Benefiting from the closed-form solution, the whole framework is trained end-to-end. Our method outperforms the state of the art in both precision and plausibility which is assessed by a new metric.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 29 of its 43 references that are in the map. First posted on arXiv 22 Feb 2023.

Builds on

29 of 43 references.

References · 29

  1. 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 692
  2. 2018Simple Baselines for Human Pose Estimation and Trackingcited by 502
  3. 2016Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervisioncited by 493
  4. 2017A simple yet effective baseline for 3d human pose estimationcited by 401
  5. 2017End-to-End Learning of Geometry and Context for Deep Stereo Regressioncited by 359
  6. 2016Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Posecited by 220
  7. 2019Semantic Graph Convolutional Networks for 3D Human Pose Regressioncited by 204
  8. 2020AANet: Adaptive Aggregation Network for Efficient Stereo Matchingcited by 202
  9. 2022Embodied Hands: Modeling and Capturing Hands and Bodies Togethercited by 179
  10. 2019Learnable Triangulation of Human Posecited by 160
  11. 2020Epipolar Transformerscited by 117
  12. 2019Self-Supervised Learning of 3D Human Pose using Multi-view Geometrycited by 98
17 more
  1. 2019Unsupervised 3D Pose Estimation with Geometric Self-Supervisioncited by 95
  2. 2021Graph Stacked Hourglass Networks for 3D Human Pose Estimationcited by 94
  3. 2019Cross View Fusion for 3D Human Pose Estimationcited by 90
  4. 2019RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimationcited by 85
  5. 2019Fast and Robust Multi-Person 3D Pose Estimation from Multiple Viewscited by 83
  6. 2020Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representationcited by 57
  7. 2015Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Videocited by 54
  8. 2017Harvesting Multiple Views for Marker-less 3D Human Pose Annotationscited by 48
  9. 2019In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representationscited by 48
  10. 2021TransFusion: Cross-view Fusion with Transformer for 3D Human Pose Estimationcited by 32
  11. 2020Fusing Wearable IMUs with Multi-View Images for Human Pose Estimation: A Geometric Approachcited by 27
  12. 2018A generalizable approach for multi-view 3D human pose regressioncited by 26
  13. 2019Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimationcited by 23
  14. 2018Deep Autoencoder for Combined Human Pose Estimation and body Model Upscalingcited by 12
  15. 2017A Kinematic Chain Space for Monocular Motion Capturecited by 8
  16. 2021An Adversarial Human Pose Estimation Network Injected with Graph Structurecited by 8
  17. 20213D Pose Estimation and Future Motion Prediction from 2D Imagescited by 8

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

6 papers.