mlsanityData to 7 Oct 2026

Human 3D Avatar Modeling with Implicit Neural Representation: A Brief Survey

arXiv 2306.03576 ↗First posted 6 Jun 2023cs.CVcited by 7

Not on the map. Why?

Abstract (arXiv)

A human 3D avatar is one of the important elements in the metaverse, and the modeling effect directly affects people's visual experience. However, the human body has a complex topology and diverse details, so it is often expensive, time-consuming, and laborious to build a satisfactory model. Recent studies have proposed a novel method, implicit neural representation, which is a continuous representation method and can describe objects with arbitrary topology at arbitrary resolution. Researchers have applied implicit neural representation to human 3D avatar modeling and obtained more excellent results than traditional methods. This paper comprehensively reviews the application of implicit neural representation in human body modeling. First, we introduce three implicit representations of occupancy field, SDF, and NeRF, and make a classification of the literature investigated in this paper. Then the application of implicit modeling methods in the body, hand, and head are compared and analyzed respectively. Finally, we point out the shortcomings of current work and provide available suggestions for researchers.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 41 of its 80 references that are in the map. First posted on arXiv 6 Jun 2023.

Builds on

41 of 80 references.

References · 41

  1. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  2. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  3. 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,471
  4. 2019PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitizationcited by 818
  5. 2020Convolutional Occupancy Networkscited by 760
  6. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 688
  7. 2020Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humanscited by 634
  8. 2020PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitizationcited by 521
  9. 2021Animatable Neural Radiance Fields for Modeling Dynamic Human Bodiescited by 361
  10. 2017Learning from Synthetic Humanscited by 358
  11. 2021ICON: Implicit Clothed humans Obtained from Normalscited by 283
  12. 20193D Morphable Face Models -- Past, Present and Futurecited by 269
29 more
  1. 2021HeadNeRF: A Real-time NeRF-based Parametric Head Modelcited by 228
  2. 2018Learning to Estimate 3D Human Pose and Shape from a Single Color Imagecited by 226
  3. 2021SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapescited by 221
  4. 2021SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networkscited by 181
  5. 2022Embodied Hands: Modeling and Capturing Hands and Bodies Togethercited by 179
  6. 2020Grasping Field: Learning Implicit Representations for Human Graspscited by 178
  7. 2021Implicit Neural Representations for Image Compressioncited by 161
  8. 2019NASA: Neural Articulated Shape Approximationcited by 149
  9. 2018BodyNet: Volumetric Inference of 3D Human Body Shapescited by 141
  10. 2020Combining Implicit Function Learning and Parametric Models for 3D Human Reconstructioncited by 133
  11. 2022Photorealistic Monocular 3D Reconstruction of Humans Wearing Clothingcited by 126
  12. 2020Geo-PIFu: Geometry and Pixel Aligned Implicit Functions for Single-view Human Reconstructioncited by 112
  13. 2021LEAP: Learning Articulated Occupancy of Peoplecited by 107
  14. 2021Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothingcited by 102
  15. 2021imGHUM: Implicit Generative Models of 3D Human Shape and Articulated Posecited by 102
  16. 2021Generative Models as Distributions of Functionscited by 89
  17. 2021H3D-Net: Few-Shot High-Fidelity 3D Head Reconstructioncited by 81
  18. 2020Neural Deformation Graphs for Globally-consistent Non-rigid Reconstructioncited by 66
  19. 2022ImFace: A Nonlinear 3D Morphable Face Model with Implicit Neural Representationscited by 64
  20. 2019Towards a complete 3D morphable model of the human headcited by 63
  21. 2022LISA: Learning Implicit Shape and Appearance of Handscited by 63
  22. 2021S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modelingcited by 59
  23. 2021A Skeleton-Driven Neural Occupancy Representation for Articulated Handscited by 50
  24. 2023Context De-confounded Emotion Recognitioncited by 34
  25. 2020Codimensional Incremental Potential Contactcited by 33
  26. 2022NeuralHDHair: Automatic High-fidelity Hair Modeling from a Single Image Using Implicit Neural Representationscited by 31
  27. 2021PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imagingcited by 14
  28. 2021Interactive Modelling of Volumetric Musculoskeletal Anatomycited by 8
  29. 2022UNIF: United Neural Implicit Functions for Clothed Human Reconstruction and Animationcited by 8

Built on by

Cited by year

Citing papers per year: 2023: 3; 2024: 1; 2025: 3.

7 papers.

  1. 2024PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observationscited by 51
  2. 2023AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perceptioncited by 39
  3. 2025Advances in Radiance Field for Dynamic Scene: From Neural Field to Gaussian Fieldcited by 4
  4. 2023Fast Satellite Tensorial Radiance Field for Multi-date Satellite Imagery of Large Sizecited by 2
  5. 2023High-Degrees-of-Freedom Dynamic Neural Fields for Robot Self-Modeling and Motion Planningcited by 1
  6. 2025MaintaAvatar: A Maintainable Avatar Based on Neural Radiance Fields by Continual Learningcited by 0
  7. 2025T-MLP: Tailed Multi-Layer Perceptron for Level-of-Detail Signal Representationcited by 0