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pro vyhledávání: '"Colbois, Laurent"'
Autor:
Colbois, Laurent, Marcel, Sébastien
Morphing attacks have diversified significantly over the past years, with new methods based on generative adversarial networks (GANs) and diffusion models posing substantial threats to face recognition systems. Recent research has demonstrated the ef
Externí odkaz:
http://arxiv.org/abs/2410.16802
Recent works have demonstrated the feasibility of inverting face recognition systems, enabling to recover convincing face images using only their embeddings. We leverage such template inversion models to develop a novel type ofdeep morphing attack ba
Externí odkaz:
http://arxiv.org/abs/2402.00695
Autor:
Colbois, Laurent, Marcel, Sébastien
Recent works have demonstrated the feasibility of GAN-based morphing attacks that reach similar success rates as more traditional landmark-based methods. This new type of "deep" morphs might require the development of new adequate detectors to protec
Externí odkaz:
http://arxiv.org/abs/2209.00404
Publikováno v:
2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access c
Externí odkaz:
http://arxiv.org/abs/2205.02496
The availability of large-scale face datasets has been key in the progress of face recognition. However, due to licensing issues or copyright infringement, some datasets are not available anymore (e.g. MS-Celeb-1M). Recent advances in Generative Adve
Externí odkaz:
http://arxiv.org/abs/2106.04215
Morphing attacks is a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access co
Externí odkaz:
http://arxiv.org/abs/2012.05344