mlsanityData to 7 Oct 2026

Estimation of 3D Human Pose Using Prior Knowledge

arXiv 2105.03807 ↗First posted 9 May 2021cs.CVcited by 2

Not on the map. Why?

Abstract (arXiv)

Estimating three-dimensional human poses from the positions of two-dimensional joints has shown promising results.However, using two-dimensional joint coordinates as input loses more information than image-based approaches and results in ambiguity.In order to overcome this problem, we combine bone length and camera parameters with two-dimensional joint coordinates for input.This combination is more discriminative than the two-dimensional joint coordinates in that it can improve the accuracy of the model's prediction depth and alleviate the ambiguity that comes from projecting three-dimensional coordinates into two-dimensional space. Furthermore, we introduce direction constraints which can better measure the difference between the ground truth and the output of the proposed model. The experimental results on the H36M show that the method performed better than other state-of-the-art three-dimensional human pose estimation approaches.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 19 of its 25 references that are in the map. First posted on arXiv 9 May 2021.

Builds on

19 of 25 references.

References · 19

  1. 2016Stacked Hourglass Networks for Human Pose Estimationcited by 913
  2. 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 692
  3. 2019VIBE: Video Inference for Human Body Pose and Shape Estimationcited by 615
  4. 2017A simple yet effective baseline for 3d human pose estimationcited by 401
  5. 20183D human pose estimation in video with temporal convolutions and semi-supervised trainingcited by 401
  6. 2019Semantic Graph Convolutional Networks for 3D Human Pose Regressioncited by 204
  7. 2017Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approachcited by 114
  8. 2018Ordinal Depth Supervision for 3D Human Pose Estimationcited by 107
  9. 2019Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Networkcited by 92
  10. 2019Cross View Fusion for 3D Human Pose Estimationcited by 90
  11. 20183D Human Pose Estimation in the Wild by Adversarial Learningcited by 86
  12. 2019RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimationcited by 85
7 more
  1. 2019Monocular 3D Human Pose Estimation by Generation and Ordinal Rankingcited by 76
  2. 2020Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wildcited by 66
  3. 2019In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representationscited by 48
  4. 2020Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image Synthesiscited by 44
  5. 2019View Invariant 3D Human Pose Estimationcited by 11
  6. 2018DRPose3D: Depth Ranking in 3D Human Pose Estimationcited by 9
  7. 2020MetaFuse: A Pre-trained Fusion Model for Human Pose Estimationcited by 9

Built on by

Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025PriorFormer: A Transformer for Real-time Monocular 3D Human Pose Estimation with Versatile Geometric Priorscited by 1
  2. 2025HiLWS: A Human-in-the-Loop Weak Supervision Framework for Curating Clinical and Home Video Data for Neurological Assessmentcited by 0