Face Recognition Systems Under Morphing Attacks: A Survey
TLDR
A conceptual categorization and metrics for an evaluation of such methods are presented, followed by a comprehensive survey of relevant publications, and technical considerations and tradeoffs of the surveyed methods are discussed.Abstract:
Recently, researchers found that the intended generalizability of (deep) face recognition systems increases their vulnerability against attacks. In particular, the attacks based on morphed face images pose a severe security risk to face recognition systems. In the last few years, the topic of (face) image morphing and automated morphing attack detection has sparked the interest of several research laboratories working in the field of biometrics and many different approaches have been published. In this paper, a conceptual categorization and metrics for an evaluation of such methods are presented, followed by a comprehensive survey of relevant publications. In addition, technical considerations and tradeoffs of the surveyed methods are discussed along with open issues and challenges in the field.read more
Citations
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Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
TL;DR: This work proposes an efficient algorithm to embed a given image into the latent space of StyleGAN, which enables semantic image editing operations that can be applied to existing photographs.
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DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection
TL;DR: This survey provides a thorough review of techniques for manipulating face images including DeepFake methods, and methods to detect such manipulations, with special attention to the latest generation of DeepFakes.
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Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
TL;DR: In this paper, an efficient algorithm was proposed to embed a given image into the latent space of StyleGAN, which enables semantic image editing operations that can be applied to existing photographs, such as image morphing, style transfer, and expression transfer.
Journal ArticleDOI
Face recognition: Past, present and future (a review)
TL;DR: The methods used to obtain and classify facial biometric data in the literature have been summarized and a taxonomy of image-based and video-based face recognition methods is given, outlining the major historical developments, and the main processing steps.
Journal ArticleDOI
Deep Face Representations for Differential Morphing Attack Detection
TL;DR: Subsets of the FERET and FRGCv2 face databases are used to create a realistic database for training and testing of MAD algorithms, and it is shown that algorithms based on deep face representations can achieve very high detection performance and robustness with respect to various post-processings.
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