Facial beauty is an intriguing and multifaceted subject that has captivated human interest, crossing cultural and scientific boundaries for centuries. In today's digital age, understanding facial beauty is no longer just an art but a sophisticated science, the analysis and enhancement of facial beauty leverage advanced technologies such as machine learning, computer vision, and biometrics. This book, "Facial Beauty Analysis: Computational Aesthetics," is based on our research and aims to offer an in-depth exploration of the latest advancements on both 2D and 3D facial beauty analysis.

By combining principles from computer vision, pattern recognition, machine learning, and deep learning, this book provides comprehensive insights into landmark detection, feature extraction, beauty prediction, and facial attractiveness enhancement. It introduces cutting-edge innovations such as geometric prior guided hybrid deep neural networks, GAN-based facial beautification, and 3D facial beauty analysis, ensuring readers are equipped with the latest advancements. The content is thoughtfully crafted to empower readers with both foundational concepts and the latest tools required to stay ahead in this rapidly evolving domain.

Targeted toward researchers, professionals, and graduate students, "Facial Beauty Analysis: Computational Aesthetics," aims to systematically cover both 2D and 3D facial beauty analysis, providing comprehensive insights into feature extraction, beauty prediction, and facial enhancement. This book offers both foundational knowledge and cutting-edge methodologies to advance the field of facial beauty analysis. Whether you're exploring the fundamentals or seeking to apply the latest technologies, this book is a valuable asset for anyone dedicated to advancing the field of facial beauty analysis.