This book presents a comprehensive review of heterogeneous face analysis
and synthesis, ranging from the theoretical and technical foundations to
various hot and emerging applications, such as cosmetic transfer,
cross-spectral hallucination and face rotation. Deep generative models
have been at the forefront of research on artificial intelligence in
recent years and have enhanced many heterogeneous face analysis tasks.
Not only has there been a constantly growing flow of related research
papers, but there have also been substantial advances in real-world
applications. Bringing these together, this book describes both the
fundamentals and applications of heterogeneous face analysis and
synthesis. Moreover, it discusses the strengths and weaknesses of
related methods and outlines future trends.
Offering a rich blend of theory and practice, the book represents a
valuable resource for students, researchers and practitioners who need
to construct face analysis systems with deep generative networks.