# PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging

arXiv: https://arxiv.org/abs/2106.10893 · HTML: https://mlsanity.com/paper/2106.10893/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 29 references that are in the map.
- First posted on arXiv 21 Jun 2021.

## Builds on (most cited first, 7 of 7)

- [V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation](https://mlsanity.com/paper/1606.04797/) (2016)
- [3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation](https://mlsanity.com/paper/1606.06650/) (2016)
- [Learning joint reconstruction of hands and manipulated objects](https://mlsanity.com/paper/1904.05767/) (2019)
- [FreiHAND: A Dataset for Markerless Capture of Hand Pose and Shape from Single RGB Images](https://mlsanity.com/paper/1909.04349/) (2019)
- [KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations](https://mlsanity.com/paper/2006.04878/) (2020)
- [DeepHandMesh: A Weakly-supervised Deep Encoder-Decoder Framework for High-fidelity Hand Mesh Modeling](https://mlsanity.com/paper/2008.08213/) (2020)
- [Fetal Pose Estimation in Volumetric MRI using a 3D Convolution Neural Network](https://mlsanity.com/paper/1907.04500/) (2019)

## Built on by (most cited first, 14 of 14)

- [Executing your Commands via Motion Diffusion in Latent Space](https://mlsanity.com/paper/2212.04048/) (2022)
- [MotionGPT: Human Motion as a Foreign Language](https://mlsanity.com/paper/2306.14795/) (2023)
- [MotionChain: Conversational Motion Controllers via Multimodal Prompts](https://mlsanity.com/paper/2404.01700/) (2024)
- [HARP: Personalized Hand Reconstruction from a Monocular RGB Video](https://mlsanity.com/paper/2212.09530/) (2022)
- [DART: Articulated Hand Model with Diverse Accessories and Rich Textures](https://mlsanity.com/paper/2210.07650/) (2022)
- [OHTA: One-shot Hand Avatar via Data-driven Implicit Priors](https://mlsanity.com/paper/2402.18969/) (2024)
- [MRI-CORE: A Foundation Model for Magnetic Resonance Imaging](https://mlsanity.com/paper/2506.12186/) (2025)
- [Human 3D Avatar Modeling with Implicit Neural Representation: A Brief Survey](https://mlsanity.com/paper/2306.03576/) (2023)
- [NIMBLE: A Non-rigid Hand Model with Bones and Muscles](https://mlsanity.com/paper/2202.04533/) (2022)
- [FIND: An Unsupervised Implicit 3D Model of Articulated Human Feet](https://mlsanity.com/paper/2210.12241/) (2022)
- [LS-GAN: Human Motion Synthesis with Latent-space GANs](https://mlsanity.com/paper/2501.01449/) (2024)
- [SCULPTOR: Skeleton-Consistent Face Creation Using a Learned Parametric Generator](https://mlsanity.com/paper/2209.06423/) (2022)
- [MaSkel: A Model for Human Whole-body X-rays Generation from Human Masking Images](https://mlsanity.com/paper/2404.09000/) (2024)
- [Mutual Adaptive Reasoning for Monocular 3D Multi-Person Pose Estimation](https://mlsanity.com/paper/2207.07900/) (2022)

## Abstract (arXiv)

Hand modeling is critical for immersive VR/AR, action understanding, or human healthcare. Existing parametric models account only for hand shape, pose, or texture, without modeling the anatomical attributes like bone, which is essential for realistic hand biomechanics analysis. In this paper, we present PIANO, the first parametric bone model of human hands from MRI data. Our PIANO model is biologically correct, simple to animate, and differentiable, achieving more anatomically precise modeling of the inner hand kinematic structure in a data-driven manner than the traditional hand models based on the outer surface only. Furthermore, our PIANO model can be applied in neural network layers to enable training with a fine-grained semantic loss, which opens up the new task of data-driven fine-grained hand bone anatomic and semantic understanding from MRI or even RGB images. We make our model publicly available.