Facial Beauty Prediction

5 papers with code • 3 benchmarks • 0 datasets

Facial beauty prediction is the task of predicting the attractiveness of a face.

( Image credit: SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction )

Most implemented papers

SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction

HCIILAB/SCUT-FBP5500-Database-Release 19 Jan 2018

Previous works have formulated the recognition of facial beauty as a specific supervised learning problem of classification, regression or ranking, which indicates that FBP is intrinsically a computation problem with multiple paradigms.

Transferring Rich Deep Features for Facial Beauty Prediction

lucasxlu/TransFBP 20 Mar 2018

Feature extraction plays a significant part in computer vision tasks.

MEBeauty: a multi-ethnic facial beauty dataset in-the-wild

fbplab/MEBeauty-database Emerging trends in Artificial Intelligence and Machine Learning 2021

Several FBP frameworks are performed on the proposed dataset and widely-used SCUT-FBP 5500 in order to compare their effectiveness on face images in constrained and unconstrained environments.

MetaFBP: Learning to Learn High-Order Predictor for Personalized Facial Beauty Prediction

metavisionlab/metafbp 23 Nov 2023

To this end, we propose a novel MetaFBP framework, in which we devise a universal feature extractor to capture the aesthetic commonality and then optimize to adapt the aesthetic individuality by shifting the decision boundary of the predictor via a meta-learning mechanism.

Facial Beauty Analysis Using Distribution Prediction and CNN Ensembles

ugail/FaciaIBeautyIEEESKIMA2023 International Conference on Software, Knowledge, Information Management and Applications (SKIMA) 2023

In addition, deep learning based FBP approaches so far use transfer learning from models trained on general classification tasks such as ImageNet.