# HairCS: Reconstructing Strand-Based Hair from Hair Cards

arXiv: https://arxiv.org/abs/2609.16465 · HTML: https://mlsanity.com/paper/2609.16465/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 55 references that are in the map.
- First posted on arXiv 15 Sep 2026.

## Builds on (most cited first, 13 of 13)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [GaussianHair: Hair Modeling and Rendering with Light-aware Gaussians](https://mlsanity.com/paper/2402.10483/) (2024)
- [HairStep: Transfer Synthetic to Real Using Strand and Depth Maps for Single-View 3D Hair Modeling](https://mlsanity.com/paper/2303.02700/) (2023)
- [Human Hair Reconstruction with Strand-Aligned 3D Gaussians](https://mlsanity.com/paper/2409.14778/) (2024)
- [NeuWigs: A Neural Dynamic Model for Volumetric Hair Capture and Animation](https://mlsanity.com/paper/2212.00613/) (2022)
- [HAAR: Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles](https://mlsanity.com/paper/2312.11666/) (2023)
- [DeepSketchHair: Deep Sketch-based 3D Hair Modeling](https://mlsanity.com/paper/1908.07198/) (2019)
- [MonoHair: High-Fidelity Hair Modeling from a Monocular Video](https://mlsanity.com/paper/2403.18356/) (2024)
- [Perm: A Parametric Representation for Multi-Style 3D Hair Modeling](https://mlsanity.com/paper/2407.19451/) (2024)
- [Video to Fully Automatic 3D Hair Model](https://mlsanity.com/paper/1809.04765/) (2018)
- [Towards Unified 3D Hair Reconstruction from Single-View Portraits](https://mlsanity.com/paper/2409.16863/) (2024)
- [Auto Hair Card Extraction for Smooth Hair with Differentiable Rendering](https://mlsanity.com/paper/2505.18805/) (2025)
- [CHARM: Control-point-based 3D Anime Hairstyle Auto-Regressive Modeling](https://mlsanity.com/paper/2509.21114/) (2025)

## Built on by (most cited first, 1 of 1)

- [HairFlow: Modeling 3D Hair Strands with Multi-Modal Conditioned Diffusion](https://mlsanity.com/paper/2610.17348/) (2026)

## Abstract (arXiv)

We present an automated pipeline that converts hair-card models into high-quality strand-based hairstyles. Given a collection of textured triangular or quad strips as input, our method produces a strand-based representation that preserves the original hairstyle while enriching it with fine-scale geometric detail and adhering to standard production requirements: strands originate from the scalp, roots are uniformly distributed, and the hair volume is plausibly filled. The resulting assets are directly compatible with strand-based rendering, physics-based simulation, and common grooming modifiers (e.g., clumping, curling, noise) for enhanced realism and artistic control. We validate our approach on a large and diverse set of hairstyles, including short and long hair, curly styles, and complex styles such as buns and ponytails.