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3D Human Pose and Shape Estimation from LiDAR Point Clouds: A Review

arXiv 2509.12197 ↗First posted 15 Sep 2025cs.CVcited by 0

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Abstract (arXiv)

In this paper, we present a comprehensive review of 3D human pose estimation and human mesh recovery from in-the-wild LiDAR point clouds. We compare existing approaches across several key dimensions, and propose a structured taxonomy to classify these methods. Following this taxonomy, we analyze each method's strengths, limitations, and design choices. In addition, (i) we perform a quantitative comparison of the three most widely used datasets, detailing their characteristics; (ii) we compile unified definitions of all evaluation metrics; and (iii) we establish benchmark tables for both tasks on these datasets to enable fair comparisons and promote progress in the field. We also outline open challenges and research directions critical for advancing LiDAR-based 3D human understanding. Moreover, we maintain an accompanying webpage that organizes papers according to our taxonomy and continuously update it with new studies: https://github.com/valeoai/3D-Human-Pose-Shape-Estimation-from-LiDAR

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 97 of its 163 references that are in the map. First posted on arXiv 15 Sep 2025.

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97 of 163 references.

References · 97

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  3. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  4. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
  5. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,715
  6. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,612
  7. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  8. 2019AMASS: Archive of Motion Capture as Surface Shapescited by 1,236
  9. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,209
  10. 2018OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,162
  11. 2017Simple Online and Realtime Tracking with a Deep Association Metriccited by 910
  12. 2023Point Transformer V3: Simpler, Faster, Strongercited by 589
38 more
  1. 2022ViTPose: Simple Vision Transformer Baselines for Human Pose Estimationcited by 456
  2. 2022PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategiescited by 436
  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. 2022Point Transformer V2: Grouped Vector Attention and Partition-based Poolingcited by 388
  6. 2020HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimationcited by 307
  7. 20213D Human Pose Estimation with Spatial and Temporal Transformerscited by 272
  8. 2019Convolutional Mesh Regression for Single-Image Human Shape Reconstructioncited by 270
  9. 2021Mesh Graphormercited by 265
  10. 2020Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Posecited by 248
  11. 2022CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimationcited by 238
  12. 2020PaMIR: Parametric Model-Conditioned Implicit Representation for Image-based Human Reconstructioncited by 231
  13. 2018Learning to Estimate 3D Human Pose and Shape from a Single Color Imagecited by 226
  14. 2016Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Posecited by 221
  15. 2020Deep Learning-Based Human Pose Estimation: A Surveycited by 207
  16. 2023WHAM: Reconstructing World-grounded Humans with Accurate 3D Motioncited by 206
  17. 2019Semantic Graph Convolutional Networks for 3D Human Pose Regressioncited by 204
  18. 2022AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Timecited by 200
  19. 2018Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimationcited by 185
  20. 2023RTMPose: Real-Time Multi-Person Pose Estimation based on MMPosecited by 175
  21. 2020Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Videocited by 163
  22. 2022MixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Videocited by 159
  23. 2018BodyNet: Volumetric Inference of 3D Human Body Shapescited by 141
  24. 2020FLOT: Scene Flow on Point Clouds Guided by Optimal Transportcited by 129
  25. 2017Compositional Human Pose Regressioncited by 124
  26. 2022Recovering 3D Human Mesh from Monocular Images: A Surveycited by 103
  27. 2017V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Mapcited by 102
  28. 2024Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shotcited by 101
  29. 2020Lidar for Autonomous Driving: The principles, challenges, and trends for automotive lidar and perception systemscited by 100
  30. 2017Self-supervised Learning of Motion Capturecited by 97
  31. 2021Graph Stacked Hourglass Networks for 3D Human Pose Estimationcited by 95
  32. 2023Diffusion-Based 3D Human Pose Estimation with Multi-Hypothesis Aggregationcited by 82
  33. 2022P-STMO: Pre-Trained Spatial Temporal Many-to-One Model for 3D Human Pose Estimationcited by 80
  34. 2019Monocular 3D Human Pose Estimation by Generation and Ordinal Rankingcited by 76
  35. 2022LidarMultiNet: Towards a Unified Multi-Task Network for LiDAR Perceptioncited by 74
  36. 20163D Human Pose Estimation from a Single Image via Distance Matrix Regressioncited by 73
  37. 2022DiffPose: Multi-hypothesis Human Pose Estimation using Diffusion modelscited by 65
  38. 2020AB3DMOT: A Baseline for 3D Multi-Object Tracking and New Evaluation Metricscited by 63

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