# GroomCap: High-Fidelity Prior-Free Hair Capture

arXiv: https://arxiv.org/abs/2409.00831 · HTML: https://mlsanity.com/paper/2409.00831/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Sep 2024.

## Built on by (most cited first, 21 of 21)

- [DiffLocks: Generating 3D Hair from a Single Image using Diffusion Models](https://mlsanity.com/paper/2505.06166/) (2025)
- [Quaffure: Real-Time Quasi-Static Neural Hair Simulation](https://mlsanity.com/paper/2412.10061/) (2024)
- [Im2Haircut: Single-view Strand-based Hair Reconstruction for Human Avatars](https://mlsanity.com/paper/2509.01469/) (2025)
- [GroomLight: Hybrid Inverse Rendering for Relightable Human Hair Appearance Modeling](https://mlsanity.com/paper/2503.10597/) (2025)
- [StrandHead: Text to Hair-Disentangled 3D Head Avatars Using Human-Centric Priors](https://mlsanity.com/paper/2412.11586/) (2024)
- [NeuralFur: Animal Fur Reconstruction From Multi-View Images](https://mlsanity.com/paper/2601.12481/) (2026)
- [HairGS: Hair Strand Reconstruction based on 3D Gaussian Splatting](https://mlsanity.com/paper/2509.07774/) (2025)
- [DGH: Dynamic Gaussian Hair](https://mlsanity.com/paper/2512.17094/) (2025)
- [PhysHead: Simulation-Ready Gaussian Head Avatars](https://mlsanity.com/paper/2604.06467/) (2026)
- [Generative Modeling with Orbit-Space Particle Flow Matching](https://mlsanity.com/paper/2605.02222/) (2026)
- [GeomHair: Reconstruction of Hair Strands from Colorless 3D Scans](https://mlsanity.com/paper/2505.05376/) (2025)
- [HairOrbit: Multi-view Aware 3D Hair Modeling from Single Portraits](https://mlsanity.com/paper/2604.02867/) (2026)
- [CGHair: Compact Gaussian Hair Reconstruction with Card Clustering](https://mlsanity.com/paper/2604.03716/) (2026)
- [HairGPT: Strand-as-Language Autoregressive Modeling for Realistic 3D Hairstyle Synthesis](https://mlsanity.com/paper/2605.08824/) (2026)
- [MoZoo:Unleashing Video Diffusion power in animal fur and muscle simulation](https://mlsanity.com/paper/2605.13857/) (2026)
- [HairLRM: Strand-based Hair Modeling via Large Reconstruction Models](https://mlsanity.com/paper/2606.15238/) (2026)
- [EfficientMonoHair: Fast Strand-Level Reconstruction from Monocular Video via Multi-View Direction Fusion](https://mlsanity.com/paper/2604.05794/) (2026)
- [Wispy to Voluminous: Prior-free Multi-view Capture of Strand-level Facial Hair](https://mlsanity.com/paper/2606.08041/) (2026)
- [Detangled: A Framework for Creating, Editing, and Inferencing Feature Rich Hair Strands](https://mlsanity.com/paper/2607.09811/) (2026)
- [Head Avatars with Dynamic Explicit Hair](https://mlsanity.com/paper/2607.23861/) (2026)
- [Inverse Rendering for Modeling with Line Primitives](https://mlsanity.com/paper/2609.00625/) (2026)

## Abstract (arXiv)

Despite recent advances in multi-view hair reconstruction, achieving strand-level precision remains a significant challenge due to inherent limitations in existing capture pipelines. We introduce GroomCap, a novel multi-view hair capture method that reconstructs faithful and high-fidelity hair geometry without relying on external data priors. To address the limitations of conventional reconstruction algorithms, we propose a neural implicit representation for hair volume that encodes high-resolution 3D orientation and occupancy from input views. This implicit hair volume is trained with a new volumetric 3D orientation rendering algorithm, coupled with 2D orientation distribution supervision, to effectively prevent the loss of structural information caused by undesired orientation blending. We further propose a Gaussian-based hair optimization strategy to refine the traced hair strands with a novel chained Gaussian representation, utilizing direct photometric supervision from images. Our results demonstrate that GroomCap is able to capture high-quality hair geometries that are not only more precise and detailed than existing methods but also versatile enough for a range of applications.