This paper delves into the vulnerability of 3D Face Recognition (3DFR) systems to face morphing attacks. While 2D Face Recognition systems have been extensively studied in terms of morphing attacks, the understanding of 3DFR systems’ vulnerability is comparatively less. The authors describe methods for generating 3D face morphs and examine their similarity scores to the contributing faces. The paper suggests that 3DFR systems are expected to be more robust against such attacks and explores potential improvements to mitigate these vulnerabilities.
Publication date: 22 Sep 2023
Project Page: Not provided
Paper: https://arxiv.org/pdf/2309.12118
