HairCS: Reconstructing Strand-Based Hair from Hair Cards

• URL: http://arxiv.org/abs/2609.16465v1
• Date: Tue, 15 Sep 2026 00:35:17 GMT
• Title: HairCS: Reconstructing Strand-Based Hair from Hair Cards
• Abstract summary: We present an automated pipeline that converts hair-card models into high-quality strand-based hairstyles.<n>Given a collection of textured triangular or quad strips as input, our method produces a strand-based representation that preserves the original hairstyle.<n>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.
• Score: 30.92919432095559
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

Related papers

• HairGPT: Strand-as-Language Autoregressive Modeling for Realistic 3D Hairstyle Synthesis [62.89988554372163]
  HairGPT is a strand-centric framework that treats strands as generative primitives.<n>It formulates realistic 3D hairstyle synthesis as a dual-decoupled autoregressive sequence modeling problem.
  arXiv  Detail & Related papers  (2026-05-09T09:19:36Z)
• CHARM: Control-point-based 3D Anime Hairstyle Auto-Regressive Modeling [43.54249989719103]
  We present CHARM, a novel parametric representation and generative framework for anime hairstyle modeling.<n> CHARM introduces a compact, invertible control-point-based parameterization, where a sequence of control points represents each hair card.<n>Built upon this representation, CHARM introduces an autoregressive generative framework that effectively generates anime hairstyles from input images or point clouds.
  arXiv  Detail & Related papers  (2025-09-25T13:00:38Z)
• HairGS: Hair Strand Reconstruction based on 3D Gaussian Splatting [50.93221272778306]
  Human hair reconstruction is a challenging problem in computer vision.<n>We extend the 3DGS framework to enable strand-level hair geometry reconstruction from multi-view images.<n>Our method robustly handles a wide range of hairstyles and achieves efficient reconstruction, typically completing within one hour.
  arXiv  Detail & Related papers  (2025-09-09T14:08:41Z)
• Im2Haircut: Single-view Strand-based Hair Reconstruction for Human Avatars [60.99229760565975]
  We present a novel approach for 3D hair reconstruction from single photographs based on a global hair prior combined with local optimization.<n>We exploit this prior to create a Gaussian-splatting-based reconstruction method that creates hairstyles from one or more images.
  arXiv  Detail & Related papers  (2025-09-01T13:38:08Z)
• DiffLocks: Generating 3D Hair from a Single Image using Diffusion Models [53.08138861924767]
  We propose DiffLocks, a novel framework that enables reconstruction of a wide variety of hairstyles directly from a single image.<n>First, we address the lack of 3D hair data by automating the creation of the largest synthetic hair dataset to date, containing 40K hairstyles.<n>By using a pretrained image backbone, our method generalizes to in-the-wild images despite being trained only on synthetic data.
  arXiv  Detail & Related papers  (2025-05-09T16:16:42Z)
• TANGLED: Generating 3D Hair Strands from Images with Arbitrary Styles and Viewpoints [38.95048174663582]
  Existing text or image-guided generation methods fail to handle the richness and complexity of diverse styles.<n>We present TANGLED, a novel approach for 3D hair strand generation that accommodates diverse image inputs across styles, viewpoints, and quantities of input views.
  arXiv  Detail & Related papers  (2025-02-10T12:26:02Z)
• Human Hair Reconstruction with Strand-Aligned 3D Gaussians [39.32397354314153]
  We introduce a new hair modeling method that uses a dual representation of classical hair strands and 3D Gaussians. In contrast to recent approaches that leverage unstructured Gaussians to model human avatars, our method reconstructs the hair using 3D polylines, or strands. Our method, named Gaussian Haircut, is evaluated on synthetic and real scenes and demonstrates state-of-the-art performance in the task of strand-based hair reconstruction.
  arXiv  Detail & Related papers  (2024-09-23T07:49:46Z)
• Perm: A Parametric Representation for Multi-Style 3D Hair Modeling [22.790597419351528]
  Perm is a learned parametric representation of human 3D hair designed to facilitate various hair-related applications.<n>We leverage our strand representation to fit and decompose hair geometry textures into low- to high-frequency hair structures.
  arXiv  Detail & Related papers  (2024-07-28T10:05:11Z)
• HAAR: Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles [85.12672855502517]
  We present HAAR, a new strand-based generative model for 3D human hairstyles. Based on textual inputs, HAAR produces 3D hairstyles that could be used as production-level assets in modern computer graphics engines.
  arXiv  Detail & Related papers  (2023-12-18T19:19:32Z)
• Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment [29.782276472922398]
  We propose a pose-invariant hairstyle transfer model equipped with latent optimization and a newly presented local-style-matching loss. Our model has strengths in transferring a hairstyle under larger pose differences and preserving local hairstyle textures.
  arXiv  Detail & Related papers  (2022-08-16T14:23:54Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.