D^3-Human: Dynamic Disentangled Digital Human from Monocular Video
Honghu Chen, Bo Peng, Yunfan Tao, Juyong Zhang
Abstract
We introduce D 3 -Human, a method for reconstructing Dynamic Disentangled Digital Human geometry from monocular videos. Past monocular video human reconstruction primarily focuses on reconstructing undecoupled clothed human bodies or only reconstructing clothing, making it difficult to apply directly in applications such as animation production. The challenge in reconstructing decoupled clothing and body lies in the occlusion caused by clothing over the body. To this end, the details of the visible area and the plausibility of the invisible area must be ensured during the reconstruction process. Our proposed method combines explicit and implicit representations to model the decoupled clothed human body, leveraging the robustness of explicit representations and the flexibility of implicit representations. Specifically, we reconstruct the visible region as SDF and propose a novel human manifold signed distance field (hmSDF) to segment the visible clothing and visible body, and then merge the visible and invisible body. Extensive experimental results demonstrate that, compared with existing reconstruction schemes, D 3 -Human can achieve high-quality decoupled reconstruction of the human body wearing different clothing, and can be directly applied to clothing transfer and animation production. Code is available at https://ustc3dv.github.io/D3Human/ .
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext e87f3833-e739-4406-855a-9645f212e3d6Cited by top-tier papers3
- Expressive Talking Human from Single-Image with Imperfect PriorsJun Xiang, Yudong Guo, Leipeng Hu, Boyang Guo et al.ICCV 2025 · 3 citations
- MonoCloth: Reconstruction and Animation of Cloth-Decoupled Human Avatars from Monocular VideosDaisheng Jin, Ying HeAAAI 2026 · 1 citation
- Neu-PiG: Neural Preconditioned Grids for Fast Dynamic Surface Reconstruction on Long SequencesJulian Kaltheuner, Hannah Dröge, Markus Plack, Patrick Stotko et al.CVPR 2026 · 1 citation
Builds on29
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 5,687 citations
- PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human DigitizationShunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima et al.ICCV 2019 · 1,411 citations
- Implicit Geometric Regularization for Learning ShapesAmos Gropp, Lior Yariv, Niv Haim, Matan Atzmon et al.ICML 2020 · 1,001 citations
- Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape SynthesisTianchang Shen, Jun Gao, Kangxue Yin, Ming-Yu Liu et al.NeurIPS 2021 · 652 citations
- Tex2Shape: Detailed Full Human Body Geometry From a Single ImageThiemo Alldieck, Gerard Pons-Moll, Christian Theobalt, Marcus A. MagnorICCV 2019 · 343 citations
Related papers
- REC-MV: REconstructing 3D Dynamic Cloth from Monocular VideosLingteng Qiu, Guanying Chen, Jiapeng Zhou, Mutian Xu et al.CVPR 2023
- DLCA-Recon: Dynamic Loose Clothing Avatar Reconstruction from Monocular VideosChunjie Luo, Fei Luo, Yusen Wang, Enxu Zhao et al.AAAI 2024 · 5 citations
- DeClotH: Decomposable 3D Cloth and Human Body Reconstruction from a Single ImageHyeongjin Nam, Donghwan Kim, Jeongtaek Oh, Kyoung Mu LeeCVPR 2025
- SelfRecon: Self Reconstruction Your Digital Avatar from Monocular VideoBoyi Jiang, Yang Hong, Hujun Bao, Juyong ZhangCVPR 2022 · 142 citations
- Structured 3D Features for Reconstructing Controllable AvatarsEnric Corona, Mihai Zanfir, Thiemo Alldieck, Eduard Gabriel Bazavan et al.CVPR 2023
