The SCUT-FBP5500 dataset is a diverse benchmark for facial beauty perception test. It includes 5500 frontal faces with diverse properties (male/female, Asian/Caucasian, ages) which are rated with beauty scores ranging from [1, 5] by 60 volunteers.
Dataset Summary
Number of instances: 5500 facial images
Demographic breakdown:
2000 Asian females
2000 Asian males
750 Caucasian females
750 Caucasian males
Beauty scores: Range from 1 to 5 (average of 60 raters)
Facial landmarks: 86 landmarks per face
Dataset Structure
image: The facial image
beauty_score: Beauty score (average rating from 60 volunteers)
race: Race of the person (Asian or Caucasian)
gender: Gender of the person (Male or Female)
image_name: Original image filename
has_landmarks: Whether facial landmarks are available for this image
Dataset Splits
The dataset provides:
Standard 60/40 train/test split
5-fold cross-validation splits (available in the original dataset)
Citation
@article{liang2017SCUT,
title = {SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction},
author = {Liang, Lingyu and Lin, Luojun and Jin, Lianwen and Xie, Duorui and Li, Mengru},
jurnal = {ICPR},
year = {2018}
}
License
The dataset was collected for research purposes. Please contact the original authors for commercial use.
Source
This dataset was created by South China University of Technology.
