mlsanityData to 7 Oct 2026

PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation

arXiv 2211.11734 ↗First posted 21 Nov 2022cs.CVcited by 18

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Abstract (arXiv)

We introduce PLIKS (Pseudo-Linear Inverse Kinematic Solver) for reconstruction of a 3D mesh of the human body from a single 2D image. Current techniques directly regress the shape, pose, and translation of a parametric model from an input image through a non-linear mapping with minimal flexibility to any external influences. We approach the task as a model-in-the-loop optimization problem. PLIKS is built on a linearized formulation of the parametric SMPL model. Using PLIKS, we can analytically reconstruct the human model via 2D pixel-aligned vertices. This enables us with the flexibility to use accurate camera calibration information when available. PLIKS offers an easy way to introduce additional constraints such as shape and translation. We present quantitative evaluations which confirm that PLIKS achieves more accurate reconstruction with greater than 10% improvement compared to other state-of-the-art methods with respect to the standard 3D human pose and shape benchmarks while also obtaining a reconstruction error improvement of 12.9 mm on the newer AGORA dataset.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 45 of its 66 references that are in the map. First posted on arXiv 21 Nov 2022.

Builds on

45 of 66 references.

References · 45

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  4. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  5. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,600
  6. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  7. 2017End-to-end Recovery of Human Shape and Posecited by 883
  8. 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 692
  9. 2019Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loopcited by 625
  10. 2018DensePose: Dense Human Pose Estimation In The Wildcited by 573
  11. 2016Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervisioncited by 493
  12. 2020End-to-End Human Pose and Mesh Reconstruction with Transformerscited by 417
33 more
  1. 2021PARE: Part Attention Regressor for 3D Human Body Estimationcited by 334
  2. 2020HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimationcited by 304
  3. 2020I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Imagecited by 274
  4. 2019Convolutional Mesh Regression for Single-Image Human Shape Reconstructioncited by 270
  5. 2021Mesh Graphormercited by 264
  6. 2020Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Posecited by 248
  7. 2022CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimationcited by 237
  8. 2018Learning to Estimate 3D Human Pose and Shape from a Single Color Imagecited by 226
  9. 2020Monocular, One-stage, Regression of Multiple 3D Peoplecited by 216
  10. 2021AGORA: Avatars in Geography Optimized for Regression Analysiscited by 203
  11. 2017Single-Shot Multi-Person 3D Pose Estimation From Monocular RGBcited by 195
  12. 2018Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimationcited by 185
  13. 2022PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Imagescited by 152
  14. 2021Putting People in their Place: Monocular Regression of 3D People in Depthcited by 141
  15. 2021SPEC: Seeing People in the Wild with an Estimated Cameracited by 134
  16. 2019Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Imagecited by 131
  17. 2018Activation Functions: Comparison of trends in Practice and Research for Deep Learningcited by 130
  18. 2020Exemplar Fine-Tuning for 3D Human Model Fitting Towards In-the-Wild 3D Human Pose Estimationcited by 113
  19. 2019DenseRaC: Joint 3D Pose and Shape Estimation by Dense Render-and-Comparecited by 100
  20. 2017Self-supervised Learning of Motion Capturecited by 97
  21. 2020Synthetic Training for Accurate 3D Human Pose and Shape Estimation in the Wildcited by 82
  22. 2020Accurate 3D Hand Pose Estimation for Whole-Body 3D Human Mesh Estimationcited by 81
  23. 2020Hierarchical Kinematic Human Mesh Recoverycited by 71
  24. 2020Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wildcited by 66
  25. 20203D Human Mesh Regression with Dense Correspondencecited by 66
  26. 2021Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenescited by 64
  27. 2021Reconstructing 3D Human Pose by Watching Humans in the Mirrorcited by 47
  28. 2020Beyond Weak Perspective for Monocular 3D Human Pose Estimationcited by 29
  29. 2021KAMA: 3D Keypoint Aware Body Mesh Articulationcited by 27
  30. 2020PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layerscited by 16
  31. 2022VirtualPose: Learning Generalizable 3D Human Pose Models from Virtual Datacited by 10
  32. 2021LASOR: Learning Accurate 3D Human Pose and Shape Via Synthetic Occlusion-Aware Data and Neural Mesh Renderingcited by 7
  33. 2021Learning Local Recurrent Models for Human Mesh Recoverycited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 7; 2025: 6; 2026: 3.

18 papers.

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  1. 2024AiOS: All-in-One-Stage Expressive Human Pose and Shape Estimationcited by 41
  2. 2023MAS: Multi-view Ancestral Sampling for 3D motion generation using 2D diffusioncited by 37
  3. 2025Reconstructing Humans with a Biomechanically Accurate Skeletoncited by 22
  4. 2024MeshPose: Unifying DensePose and 3D Body Mesh reconstructioncited by 8
  5. 2024Human Mesh Recovery from Arbitrary Multi-view Imagescited by 5
  6. 2024NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Human Pose Estimation in Top-View Fisheye Imagescited by 2
  7. 2024Leveraging Anthropometric Measurements to Improve Human Mesh Estimation and Ensure Consistent Body Shapescited by 2
  8. 2025Learnable SMPLify: A Neural Solution for Optimization-Free Human Pose Inverse Kinematicscited by 2
  9. 2025PersPose: 3D Human Pose Estimation with Perspective Encoding and Perspective Rotationcited by 2
  10. 2024Incorporating Test-Time Optimization into Training with Dual Networks for Human Mesh Recoverycited by 1
  11. 2025PoseSyn: Synthesizing Diverse 3D Pose Data from In-the-Wild 2D Datacited by 1
  12. 2025MobileOcc: A Human-Aware Semantic Occupancy Dataset for Mobile Robotscited by 1
6 more
  1. 2026Registration-Free Learnable Multi-View Capture of Faces in Dense Semantic Correspondencecited by 1
  2. 2023Two Views Are Better than One: Monocular 3D Pose Estimation with Multiview Consistencycited by 0
  3. 2024Multi-RoI Human Mesh Recovery with Camera Consistency and Contrastive Lossescited by 0
  4. 2025L-SR1: Learned Symmetric-Rank-One Preconditioningcited by 0
  5. 2026MoPO: Incorporating Motion Prior for Occluded Human Mesh Recoverycited by 0
  6. 2026Again-Pose: Anchor-Guided Adaptive Inter-Frame Motion Cues Propagating for High-quality Human Pose Reconstructioncited by 0