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# Gaussian Haircut：使用股线对齐 3D 高斯模型进行人体头发重建
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# Gaussian Haircut: Human Hair Reconstruction with Strand-Aligned 3D Gaussians
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[**论文**](https://arxiv.org/abs/2409.14778) | [**项目页面**](https://eth-ait.github.io/GaussianHaircut/)
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[**中文**](README_CN.md) | [**English**](README.md)
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本仓库包含了 Gaussian Haircut 的官方实现，这是一种基于股线的人体头发重建方法，用于单目视频。
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This repository contains the official implementation of Gaussian Haircut, a strand-based human hair reconstruction method from monocular video.
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## 预览
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[**Paper**](https://arxiv.org/abs/2409.14778) | [**Project Page**](https://eth-ait.github.io/GaussianHaircut/)
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重建过程包括以下主要阶段：
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## Overview
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1. **预处理阶段**
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- 视频帧提取和整理
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- COLMAP相机重建
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- 头发和身体分割
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- 图像质量评估和筛选
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- 方向图计算
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- 人脸关键点检测
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- FLAME头部模型拟合
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The reconstruction process includes the following main stages:
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2. **重建阶段**
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- 3D高斯体重建
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- FLAME网格拟合
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- 场景裁剪和优化
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- 头发股线重建
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1. **Preprocessing Stage**
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- Video frame extraction and organization
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- COLMAP camera reconstruction
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- Hair and body segmentation
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- Image quality assessment and filtering
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- Orientation map calculation
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- Facial keypoint detection
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- FLAME head model fitting
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3. **可视化阶段**
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- 导出重建的股线
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- Blender渲染可视化
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- 生成结果视频
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2. **Reconstruction Stage**
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- 3D Gaussian reconstruction
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- FLAME mesh fitting
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- Scene cropping and optimization
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- Hair strand reconstruction
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预期输出：
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3. **Visualization Stage**
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- Export reconstructed strands
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- Blender rendering visualization
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- Generate result video
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Expected output:
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```
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[your_scene_folder]/
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├── raw.mp4 # 输入视频
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├── 3d_gaussian_splatting/ # 3D高斯体重建结果
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├── flame_fitting/ # FLAME头部模型拟合结果
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├── strands_reconstruction/ # 头发股线重建中间结果
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├── curves_reconstruction/ # 最终头发股线结果
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└── visualization/ # 渲染结果和视频
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├── raw.mp4 # Input video
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├── 3d_gaussian_splatting/ # 3D Gaussian reconstruction results
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├── flame_fitting/ # FLAME head model fitting results
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├── strands_reconstruction/ # Hair strand reconstruction intermediate results
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├── curves_reconstruction/ # Final hair strand results
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└── visualization/ # Rendering results and video
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```
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## 入门指南
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README_CN.md
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# Gaussian Haircut：使用股线对齐 3D 高斯模型进行人体头发重建
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[**中文**](README_CN.md) | [**English**](README.md)
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本仓库包含了 Gaussian Haircut 的官方实现，这是一种基于股线的人体头发重建方法，用于单目视频。
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[**论文**](https://arxiv.org/abs/2409.14778) | [**项目页面**](https://eth-ait.github.io/GaussianHaircut/)
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## 概述
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重建过程包括以下主要阶段：
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1. **预处理阶段**
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- 视频帧提取和整理
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- COLMAP相机重建
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- 头发和身体分割
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- 图像质量评估和筛选
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- 方向图计算
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- 人脸关键点检测
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- FLAME头部模型拟合
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2. **重建阶段**
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- 3D高斯体重建
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- FLAME网格拟合
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- 场景裁剪和优化
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- 头发股线重建
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3. **可视化阶段**
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- 导出重建的股线
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- Blender渲染可视化
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- 生成结果视频
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预期输出：
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```
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[your_scene_folder]/
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├── raw.mp4 # 输入视频
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├── 3d_gaussian_splatting/ # 3D高斯体重建结果
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├── flame_fitting/ # FLAME头部模型拟合结果
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├── strands_reconstruction/ # 头发股线重建中间结果
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├── curves_reconstruction/ # 最终头发股线结果
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└── visualization/ # 渲染结果和视频
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```
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## 安装指南
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### Windows 平台
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1. **安装 CUDA 11.8**
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- 从 https://developer.nvidia.com/cuda-11-8-0-download-archive 下载并安装
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- 默认安装路径：C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8
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- 确保CUDA版本与系统兼容
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2. **安装 Blender 3.6**
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- 从 https://www.blender.org/download/lts/3-6 下载并安装
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- 默认安装路径：C:\Program Files\Blender Foundation\Blender 3.6
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3. **安装 Visual Studio 2019 Build Tools**
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- 从 https://visualstudio.microsoft.com/vs/older-downloads/ 下载并安装
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- 选择"C++构建工具"工作负载
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- 默认安装路径：C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools
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4. **安装 COLMAP**
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- 从 https://github.com/colmap/colmap/releases 下载并安装
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- 下载CUDA版本的COLMAP (例如：COLMAP-3.8-windows-cuda.zip)
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- 解压到不含空格的路径 (例如：C:\COLMAP)
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- 将COLMAP目录添加到系统PATH:
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1. 打开"系统属性" > "环境变量"
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2. 在"系统变量"中找到"Path"
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3. 点击"编辑" > "新建"
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4. 添加COLMAP目录路径
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5. 点击"确定"保存
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- 重启终端使PATH生效
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5. **安装 7-Zip**
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- 从 https://7-zip.org/ 下载并安装
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- 将7-Zip安装目录添加到系统PATH:
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1. 打开"系统属性" > "环境变量"
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2. 在"系统变量"中找到"Path"
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3. 点击"编辑" > "新建"
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4. 添加7-Zip安装目录(默认为C:\Program Files\7-Zip)
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5. 点击"确定"保存
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- 重启终端使PATH生效
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6. **下载预训练模型和资源**
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```cmd
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git clone https://github.com/Jeffreytsai1004/GaussianHairCut
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cd GaussianHairCut
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# 在PowerShell中运行:
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# 脚本会自动安装gdown并下载所需资源
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.\download_resource.bat
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```
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注意：
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- 下载过程可能需要几分钟到几十分钟，取决于网络速度
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- 如果下载失败，可以重新运行脚本
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- 确保有稳定的网络连接
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7. **运行安装和重建脚本**
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```cmd
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# 运行安装脚本
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.\install.bat
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# 运行重建脚本
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.\run.bat
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```
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## 使用说明
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1. **录制单目视频**
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- 参考项目页面上的示例视频
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- 录制要求：
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* 拍摄对象应缓慢转动头部，确保捕捉到所有角度
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* 保持头发和面部清晰可见
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* 避免快速移动导致的运动模糊
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* 保持光照条件稳定
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* 建议视频长度：10-20秒
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* 建议分辨率：1920x1080或更高
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2. **设置重建场景目录**
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```cmd
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# 在CMD中运行:
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set PROJECT_DIR=[path\to\]GaussianHaircut
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set DATA_PATH=[path\to\scene\folder]
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run.bat
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# 或在PowerShell中运行:
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$env:PROJECT_DIR="[path\to\]GaussianHaircut"
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$env:DATA_PATH="[path\to\scene\folder]"
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.\run.bat
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```
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注意：
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- DATA_PATH 应指向包含 raw.mp4 的目录
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- 目录路径不应包含空格或特殊字符
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- 确保有足够的磁盘空间(建议至少20GB)
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## 许可证
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此代码基于 3D Gaussian Splatting 项目。有关条款和条件，请参阅 LICENSE_3DGS。其余代码根据 CC BY-NC-SA 4.0 分发。
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## 引用
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如果此代码对您的项目有帮助，请引用以下论文：
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```bibtex
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@inproceedings{zakharov2024gh,
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title = {Human Hair Reconstruction with Strand-Aligned 3D Gaussians},
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author = {Zakharov, Egor and Sklyarova, Vanessa and Black, Michael J and Nam, Giljoo and Thies, Justus and Hilliges, Otmar},
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booktitle = {European Conference of Computer Vision (ECCV)},
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year = {2024}
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}
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```
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## 相关项目
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- [3D Gaussian Splatting](https://github.com/graphdeco-inria/gaussian-splatting)
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- [Neural Haircut](https://github.com/SamsungLabs/NeuralHaircut): FLAME 拟合管线、股线先验和发型扩散先验
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- [HAAR](https://github.com/Vanessik/HAAR): 头发上采样
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- [Matte-Anything](https://github.com/hustvl/Matte-Anything): 头发和身体分割
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- [PIXIE](https://github.com/yfeng95/PIXIE): FLAME 拟合的初始化
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- [Face-Alignment](https://github.com/1adrianb/face-alignment), [OpenPose](https://github.com/CMU-Perceptual-Computing-Lab/openpose): 用于 FLAME 拟合的关键点检测
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