mlsanityData to 7 Oct 2026

Building Statistical Shape Spaces for 3D Human Modeling

arXiv 1503.05860 ↗First posted 19 Mar 2015cs.CVcited by 47

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Abstract (arXiv)

Statistical models of 3D human shape and pose learned from scan databases have developed into valuable tools to solve a variety of vision and graphics problems. Unfortunately, most publicly available models are of limited expressiveness as they were learned on very small databases that hardly reflect the true variety in human body shapes. In this paper, we contribute by rebuilding a widely used statistical body representation from the largest commercially available scan database, and making the resulting model available to the community (visit http://humanshape.mpi-inf.mpg.de). As preprocessing several thousand scans for learning the model is a challenge in itself, we contribute by developing robust best practice solutions for scan alignment that quantitatively lead to the best learned models. We make implementations of these preprocessing steps also publicly available. We extensively evaluate the improved accuracy and generality of our new model, and show its improved performance for human body reconstruction from sparse input data.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Mar 2015.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 13; 2023: 9; 2024: 5; 2025: 9; 2026: 2.

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  1. 2021imGHUM: Implicit Generative Models of 3D Human Shape and Articulated Posecited by 102
  2. 2022A Survey of Non-Rigid 3D Registrationcited by 59
  3. 2021DPFM: Deep Partial Functional Mapscited by 58
  4. 2022AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatarscited by 55
  5. 2022Being Comes from Not-being: Open-vocabulary Text-to-Motion Generation with Wordless Trainingcited by 45
  6. 2021Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registrationcited by 41
  7. 2021Adversarial Parametric Pose Priorcited by 38
  8. 2022Differentiable Dynamics for Articulated 3d Human Motion Reconstructioncited by 38
  9. 2022Learned Vertex Descent: A New Direction for 3D Human Model Fittingcited by 37
  10. 2022Trajectory Optimization for Physics-Based Reconstruction of 3d Human Pose from Monocular Videocited by 37
  11. 2022Deep Orientation-Aware Functional Maps: Tackling Symmetry Issues in Shape Matchingcited by 36
  12. 2024Harmony4D: A Video Dataset for In-The-Wild Close Human Interactionscited by 31
35 more
  1. 2022Bending Graphs: Hierarchical Shape Matching using Gated Optimal Transportcited by 24
  2. 2021Learning Compositional Representation for 4D Captures with Neural ODEcited by 22
  3. 2022SUPR: A Sparse Unified Part-Based Human Representationcited by 21
  4. 2023Understanding and Improving Features Learned in Deep Functional Mapscited by 20
  5. 2023NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matchingcited by 18
  6. 2023Generalizing Neural Human Fitting to Unseen Poses With Articulated SE(3) Equivariancecited by 14
  7. 2023Neural Semantic Surface Mapscited by 13
  8. 2023BOSS: Bones, Organs and Skin Shape Modelcited by 12
  9. 2022Human Image Generation: A Comprehensive Surveycited by 11
  10. 2025ETCH: Generalizing Body Fitting to Clothed Humans via Equivariant Tightnesscited by 9
  11. 2025VolumetricSMPL: A Neural Volumetric Body Model for Efficient Interactions, Contacts, and Collisionscited by 9
  12. 2022BaRe-ESA: A Riemannian Framework for Unregistered Human Body Shapescited by 7
  13. 2024Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstructioncited by 7
  14. 2022MedalCare-XL: 16,900 healthy and pathological 12 lead ECGs obtained through electrophysiological simulationscited by 6
  15. 2026SOMA: Unifying Parametric Human Body Modelscited by 6
  16. 2021Learning Anthropometry from Rendered Humanscited by 5
  17. 2021A structured latent space for human body motion generationcited by 5
  18. 2024Semantic Human Mesh Reconstruction with Texturescited by 5
  19. 2021Adjoint Rigid Transform Network: Task-conditioned Alignment of 3D Shapescited by 4
  20. 2021A Neural Anthropometer Learning from Body Dimensions Computed on Human 3D Meshescited by 2
  21. 2023Mesh Strikes Back: Fast and Efficient Human Reconstruction from RGB videoscited by 2
  22. 2024Personalized Topology-Informed Localization of Standard 12-Lead ECG Electrode Placement from Incomplete Cardiac MRIs for Efficient Cardiac Digital Twinscited by 2
  23. 2024Self Supervised Networks for Learning Latent Space Representations of Human Body Scans and Motionscited by 2
  24. 2025Neural Descriptors: Self-Supervised Learning of Robust Local Surface Descriptors Using Polynomial Patchescited by 2
  25. 2025D-Garment: Physically Grounded Latent Diffusion for Dynamic Garment Deformationscited by 2
  26. 2023Unsupervised Representation Learning for Diverse Deformable Shape Collectionscited by 1
  27. 2023TailorMe: Self-Supervised Learning of an Anatomically Constrained Volumetric Human Shape Modelcited by 1
  28. 2025Pose-independent 3D Anthropometry from Sparse Datacited by 1
  29. 2025Advances in 4D Generation: A Surveycited by 1
  30. 2026Learning geometry-dependent lead-field operators for forward ECG modelingcited by 1
  31. 2022Adjustable Method Based on Body Parts for Improving the Accuracy of 3D Reconstruction in Visually Important Body Parts from Silhouettescited by 0
  32. 2023Anatomical basis of sex differences in the electrocardiogram identified by three-dimensional torso-heart imaging reconstruction pipelinecited by 0
  33. 2025S2MNet: Speckle-To-Mesh Net for Three-Dimensional Cardiac Morphology Reconstruction via Echocardiogramcited by 0
  34. 2025Disentangled Human Body Representation Based on Unsupervised Semantic-Aware Learningcited by 0
  35. 2025Matching Shapes Under Different Topologies: A Topology-Adaptive Deformation Guided Approachcited by 0