advances face presentation attack von wan jun (4 Ergebnisse)

Zustand: New. In.

Zustand: Wie Neu. Zustandsbeschreibung: leichte Lagerspuren/minor shelfwear. By Jun Wan, Guodong Guo, Sergio Escalera, Hugo Jair Escalante and Stan Z. Li. The book presents a thorough review and evaluation of current techniques and identifies those that have achieved the highest level of performance in a series of ChaLearn face anti-spoofing challenges at CVPR and ICCV. The authors also highlight directions for future research in face-anti-spoofing that would lead to progress in the field. Second Edition. VIII,111 Seiten mit 48 Farb- und 52 s/w-Abb., gebunden (Synthesis Lectures on Computer Vision/Springer-Verlag 2023). Statt EUR 42,79. Gewicht: 344 g - Gebunden/Gebundene Ausgabe.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book revises and expands upon the prior edition of Multi-Modal Face Presentation Attack Detection. The authors begin with fundamental and foundational information on face spoofing attack detection, explaining why the computer vision community has intensively studied it for the last decade. The authors also discuss the reasons that cause face anti-spoofing to be essential for preventing security breaches in face recognition systems. In addition, the book describes the factors that make it difficult to design effective methods of face presentation attack detection challenges. The book presents a thorough review and evaluation of current techniques and identifies those that have achieved the highest level of performance in a series of ChaLearn face anti-spoofing challenges at CVPR and ICCV. The authors also highlight directions for future research in face anti-spoofing that would lead to progress in the field. Additional analysis, new methodologies, and a more comprehensive survey of solutions are included in this new edition.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book revises and expands upon the prior edition of Multi-Modal Face Presentation Attack Detection. The authors begin with fundamental and foundational information on face spoofing attack detection, explaining why the computer vision community has intensively studied it for the last decade. The authors also discuss the reasons that cause face anti-spoofing to be essential for preventing security breaches in face recognition systems. In addition, the book describes the factors that make it difficult to design effective methods of face presentation attack detection challenges. The book presents a thorough review and evaluation of current techniques and identifies those that have achieved the highest level of performance in a series of ChaLearn face anti-spoofing challenges at CVPR and ICCV. The authors also highlight directions for future research in face anti-spoofing that would lead to progress in the field. Additional analysis, new methodologies, and a more comprehensive survey of solutions are included in this new edition.