arXiv · 2104.06885
CelebHair: A New Large-Scale Dataset for Hairstyle Recommendation based on CelebA
Abstract
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.
Explore related subjects
Keep this discovery
Yutao Chen, Yuxuan Zhang, Zhongrui Huang, Zhenyao Luo, Jinpeng Chen. 2021-04-14. CelebHair: A New Large-Scale Dataset for Hairstyle Recommendation based on CelebA. https://arxiv.org/abs/2104.06885
Cite the original work for its findings. Save a collection to share your selection of sources.