README.md

metadata

license: other
task_categories:
  - image-classification
  - image-regression
task_ids:
  - facial-beauty-prediction
language:
  - en
tags:
  - beauty-prediction
  - face-analysis
  - facial-beauty
pretty_name: SCUT-FBP5500
size_categories:
  - 1K<n<10K

SCUT-FBP5500 Dataset

Dataset Description

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.

For any questions about this database, please contact the authors by sending email to lianwen.jin@gmail.com and lianglysky@gmail.com.