# K-Hairstyle: A Large-scale Korean Hairstyle Dataset for Virtual Hair Editing and Hairstyle Classification

arXiv: https://arxiv.org/abs/2102.06288 · HTML: https://mlsanity.com/paper/2102.06288/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 18 references that are in the map.
- First posted on arXiv 11 Feb 2021.

## Builds on (most cited first, 12 of 12)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Feature Pyramid Networks for Object Detection](https://mlsanity.com/paper/1612.03144/) (2016)
- [Deep Learning Face Attributes in the Wild](https://mlsanity.com/paper/1411.7766/) (2014)
- [Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation](https://mlsanity.com/paper/1802.02611/) (2018)
- [Wide Residual Networks](https://mlsanity.com/paper/1605.07146/) (2016)
- [Pyramid Scene Parsing Network](https://mlsanity.com/paper/1612.01105/) (2016)
- [StarGAN v2: Diverse Image Synthesis for Multiple Domains](https://mlsanity.com/paper/1912.01865/) (2019)
- [MaskGAN: Towards Diverse and Interactive Facial Image Manipulation](https://mlsanity.com/paper/1907.11922/) (2019)
- [Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrieval](https://mlsanity.com/paper/2004.01804/) (2020)
- [GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium](https://mlsanity.com/paper/1706.08500/) (2017)
- [Pyramid Attention Network for Semantic Segmentation](https://mlsanity.com/paper/1805.10180/) (2018)

## Built on by (most cited first, 18 of 18)

- [PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360circ](https://mlsanity.com/paper/2303.13071/) (2023)
- [SphereHead: Stable 3D Full-head Synthesis with Spherical Tri-plane Representation](https://mlsanity.com/paper/2404.05680/) (2024)
- [Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment](https://mlsanity.com/paper/2208.07765/) (2022)
- [3D-aware Blending with Generative NeRFs](https://mlsanity.com/paper/2302.06608/) (2023)
- [Automatic Animation of Hair Blowing in Still Portrait Photos](https://mlsanity.com/paper/2309.14207/) (2023)
- [HairFIT: Pose-Invariant Hairstyle Transfer via Flow-based Hair Alignment and Semantic-Region-Aware Inpainting](https://mlsanity.com/paper/2206.08585/) (2022)
- [Towards Unified 3D Hair Reconstruction from Single-View Portraits](https://mlsanity.com/paper/2409.16863/) (2024)
- [What to Preserve and What to Transfer: Faithful, Identity-Preserving Diffusion-based Hairstyle Transfer](https://mlsanity.com/paper/2408.16450/) (2024)
- [StyleGAN Salon: Multi-View Latent Optimization for Pose-Invariant Hairstyle Transfer](https://mlsanity.com/paper/2304.02744/) (2023)
- [PanoLAM: Large Avatar Model for Gaussian Full-Head Synthesis from One-shot Unposed Image](https://mlsanity.com/paper/2509.07552/) (2025)
- [HyPlaneHead: Rethinking Tri-plane-like Representations in Full-Head Image Synthesis](https://mlsanity.com/paper/2509.16748/) (2025)
- [Hairmony: Fairness-aware hairstyle classification](https://mlsanity.com/paper/2410.11528/) (2024)
- [HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion](https://mlsanity.com/paper/2410.21789/) (2024)
- [Real-time Virtual-Try-On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Renderers](https://mlsanity.com/paper/2205.06305/) (2022)
- [Tag-based annotation creates better avatars](https://mlsanity.com/paper/2302.07354/) (2023)
- [AvatarBack: Back-Head Generation for Complete 3D Avatars from Front-View Images](https://mlsanity.com/paper/2508.20623/) (2025)
- [CylinderPlane: Nested Cylinder Representation for 3D-aware Image Generation](https://mlsanity.com/paper/2507.15606/) (2025)
- [TurboPortrait3D: Single-step diffusion-based fast portrait novel-view synthesis](https://mlsanity.com/paper/2510.23929/) (2025)

## Abstract (arXiv)

The hair and beauty industry is a fast-growing industry. This led to the development of various applications, such as virtual hair dyeing or hairstyle transfer, to satisfy the customer's needs. Although several hairstyle datasets are available for these applications, they often consist of a relatively small number of images with low resolution, thus limiting their performance on high-quality hair editing. In response, we introduce a novel large-scale Korean hairstyle dataset, K-hairstyle, containing 500,000 high-resolution images. In addition, K-hairstyle includes various hair attributes annotated by Korean expert hairstylists as well as hair segmentation masks. We validate the effectiveness of our dataset via several applications, such as hair dyeing, hairstyle transfer, and hairstyle classification. K-hairstyle is publicly available at https://psh01087.github.io/K-Hairstyle/.