Facial attractiveness plays a significant role in various aspects of life, from social interactions to professional opportunities. This project delves into the complex interplay of facial features and their impact on perceived attractiveness.
In our pursuit of understanding facial ratings, we delve into the Multi-Ethnic Dataset, an expansive repository capturing the diverse spectrum of human faces. Through data-driven exploration, we aim to unravel the intricacies of facial aesthetics and perceptions of attractiveness. Our journey unfolds across four distinct domains, each offering unique insights into the realm of facial ratings:
We conduct a comprehensive examination of the ratings assigned to faces within the dataset, employing statistical tools and visualization techniques to uncover underlying patterns and trends.
File : Facial_ratings_analysis.ipynb
Utilizing feature extraction algorithms and machine learning methodologies, we seek to identify the subtle facial attributes that correlate with varying degrees of attractiveness.
File : Incoming
Through the construction of predictive models, we endeavor to estimate facial attractiveness ratings with precision, leveraging the wealth of data encapsulated within the Multi-Ethnic Dataset.
File : incoming
Employing generative algorithms and deep learning architectures, we explore the realm of synthetic facial generation, crafting virtual visages imbued with predetermined levels of attractiveness.
File: incoming