mlsanityData to 7 Oct 2026

Deep learning for 3D human pose estimation and mesh recovery: A survey

arXiv 2402.18844 ↗First posted 29 Feb 2024cs.CV cs.MMcited by 11

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Abstract (arXiv)

3D human pose estimation and mesh recovery have attracted widespread research interest in many areas, such as computer vision, autonomous driving, and robotics. Deep learning on 3D human pose estimation and mesh recovery has recently thrived, with numerous methods proposed to address different problems in this area. In this paper, to stimulate future research, we present a comprehensive review of recent progress over the past five years in deep learning methods for this area by delving into over 200 references. To the best of our knowledge, this survey is arguably the first to comprehensively cover deep learning methods for 3D human pose estimation, including both single-person and multi-person approaches, as well as human mesh recovery, encompassing methods based on explicit models and implicit representations. We also present comparative results on several publicly available datasets, together with insightful observations and inspiring future research directions. A regularly updated project page can be found at https://github.com/liuyangme/SOTA-3DHPE-HMR.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 63 of its 99 references that are in the map. First posted on arXiv 29 Feb 2024.

Builds on

63 of 99 references.

References · 63

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38 more
  1. 2020Deep Learning-Based Human Pose Estimation: A Surveycited by 205
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  15. 2022Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformerscited by 81
  16. 2022P-STMO: Pre-Trained Spatial Temporal Many-to-One Model for 3D Human Pose Estimationcited by 80
  17. 2020Monocular Real-Time Volumetric Performance Capturecited by 74
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  38. 2021Human Pose and Shape Estimation from Single Polarization Imagescited by 13

50 most cited of 63 All 63 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 7; 2026: 3.

11 papers.

  1. 2024A Survey on 3D Egocentric Human Pose Estimationcited by 8
  2. 2025M4Human: A Large-Scale Multimodal mmWave Radar Benchmark for Human Mesh Reconstructioncited by 6
  3. 2025Advances in Radiance Field for Dynamic Scene: From Neural Field to Gaussian Fieldcited by 4
  4. 2025Dynamic Graph CNN with Jacobi Kolmogorov-Arnold Networks for 3D Classification of Point Setscited by 0
  5. 20253D Human Pose and Shape Estimation from LiDAR Point Clouds: A Reviewcited by 0
  6. 2025On the Use of Hierarchical Vision Foundation Models for Low-Cost Human Mesh Recovery and Pose Estimationcited by 0
  7. 2025PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimationcited by 0
  8. 2025A Topology-Aware Graph Convolutional Network for Human Pose Similarity and Action Quality Assessmentcited by 0
  9. 2026A Study on Real-time Object Detection using Deep Learningcited by 0
  10. 2026SEAL-pose: Enhancing 3D Human Pose Estimation via a Learned Loss for Structural Consistencycited by 0
  11. 2026Chatting about Upper-Body Expressive Human Pose and Shape Estimationcited by 0