• Title: Handbook of Digital Face Manipulation and Detection: From DeepFakes to Morphing Attacks
• Author(s) Christian Rathgeb, Ruben Tolosana, Ruben Vera-Rodriguez, Christoph Busch
• Publisher: Springer; 1st ed. (February 1, 2022); eBook (Creative Commons Licensed)
• License(s): CC BY 4.0
• Paperback: 500 pages
• eBook: PDF and ePub
• Language: English
• ISBN-10/ASIN: 3030876667
• ISBN-13: 978-3030876661
• Share This:  

Book Description

This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the both biometrics and media forensics fields including contributions from academia and industry.

Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers.

• N/A

• Amazon

• Programming/Engineering Handbooks
• Digital and Computer Forensics
• Computer Vision, Machine Vision, and Image Processing
• Deep Learning and Neural Networks
• Machine Learning
• Computer and Information Security

• Handbook of Digital Face Manipulation and Detection: From DeepFakes to Morphing Attacks
• The Mirror Site (1) - PDF

• Portraits of Automated Facial Recognition (Lila Lee-Morrison)

  Automated facial recognition algorithms are increasingly intervening in society. This book offers a unique analysis of these algorithms from a critical visual culture studies perspective.

• Recent Advances in Face Recognition (Kresimir Delac, et al)

  This goal of this book is to provide the reader with the most up to date research performed in automatic face recognition. The chapters presented use innovative approaches to deal with a wide variety of unsolved issues.

• Pattern Recognition and Machine Learning (Christopher Bishop)

  This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible.

• Computer Vision: Algorithms and Applications, Second Edition

  This book explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications as well as for fun, consumer-level tasks.

• Dive into Deep Learning (Aston Zhang, et al.)

  This is an open source, interactive book provided in a unique form factor that integrates text, mathematics and code, now supports the TensorFlow, PyTorch, and Apache MXNet programming frameworks, drafted entirely through Jupyter notebooks.

• The Hundred-Page Machine Learning Book (Andriy Burkov)

  Everything you really need to know in Machine Learning in a hundred pages! This book provides a great practical guide to get started and execute on ML within a few days without necessarily knowing much about ML apriori.

• Multimedia Fingerprinting Forensics for Traitor Tracing (K.J. Liu)

  This book describes the framework of multimedia fingerprinting by providing readers with a broader view of the evolution of the young field of multimedia forensics. It covers the essential aspects of research in this emerging technology.

• Applied Bioinformatics (David A. Hendrix)

  This book is designed to introduce students with little to no programming experience to the concepts and methodologies of bioinformatics, and contemporary software applications. It will deal with the analysis of nucleic acid sequence data.

• Natural Image Statistics in Digital Image Forensics (Siwei Lyu)

  This book provides the first general framework, based on universal statistical properties of natural images, of detecting tampering and authenticating digital images that has been successfully applied to three problems in digital image forensics.

• A Field Guide to 'Fake News' and Other Information Disorders

  Post under Social Media and Social Networks and Big Data on Sat Dec 03, 2022
  

  The book explores the use of digital methods to study false viral news, political memes, trolling practices and their social life online. It responds to an increasing demand for understanding the interplay between digital platforms, misleading information, etc.