CelebHair：基于CelebA的大规模发型推荐数据集
CelebHair: A New Large-Scale Dataset for Hairstyle Recommendation based on CelebA
摘要：
在本文中，我们提出了一个新的大规模的发型推荐数据集，CelebHair，基于名人面部属性数据集，CelebA。我们的数据集继承了CelebA的大部分面部图像以及一些与美容相关的面部属性。此外，我们采用了面部标志检测技术来提取额外的特征，如鼻子长度和瞳孔距离，以及用于面部形状和发型分类的深度卷积神经网络。实证比较表明，我们的数据集的优越性，其他现有的发型相关的数据集的品种，准确性和体积。对数据集进行了分析和实验，以评估其鲁棒性和可用性。
英文摘要：
In this paper, we present a new large-scale dataset for hairstyle recommendation, CelebHair, based on the celebrity facial attributes dataset, CelebA. Our dataset inherited the majority of facial images along with some beauty-related facial attributes from CelebA. Additionally, we employed facial landmark detection techniques to extract extra features such as nose length and pupillary distance, and deep convolutional neural networks for face shape and hairstyle classification. Empirical comparison has demonstrated the superiority of our dataset to other existing hairstyle-related datasets regarding variety, veracity, and volume. Analysis and experiments have been conducted on the dataset in order to evaluate its robustness and usability.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
