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インサイト - Face Morphing Attacks
Fast-DiM: Towards Fast Diffusion Morphs in Face Recognition Systems
Fast-DiM proposes a novel morphing method to reduce Network Function Evaluations (NFE) while maintaining performance in face recognition systems.
Fast-DiM: Towards Fast Diffusion Morphs in Face Recognition Systems
Diffusion Morphs (DiM) can be optimized for faster creation with reduced Network Function Evaluations (NFE).
Generating Highly Effective Face Morphing Attacks using Latent Semantic Disentanglement in StyleGAN
The proposed MLSD-GAN method can generate high-quality face morphing attacks that pose a significant threat to deep learning-based face recognition systems.
LADIMO: A Novel Approach to Face Morphing Using Latent Diffusion Models for Biometric Template Inversion
This research paper introduces LADIMO, a new method for generating realistic face morphs by inverting biometric templates using Latent Diffusion Models, posing a significant threat to Facial Recognition Systems (FRS) and highlighting the need for improved security measures.
