FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live Images

• URL: http://arxiv.org/abs/2505.07530v3
• Date: Wed, 16 Jul 2025 14:20:45 GMT
• Title: FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live Images
• Authors: Raul Ismayilov, Dzemila Sero, Luuk Spreeuwers,
• Abstract summary: We introduce FLUXSynID, a framework for generating high-resolution synthetic face datasets.<n>We generate synthetic faces with user-defined identity attribute distributions, offering both document-style and trusted live capture images.<n>Our work is publicly released to support biometric research, including face recognition and morphing attack detection.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Synthetic face datasets are increasingly used to overcome the limitations of real-world biometric data, including privacy concerns, demographic imbalance, and high collection costs. However, many existing methods lack fine-grained control over identity attributes and fail to produce paired, identity-consistent images under structured capture conditions. We introduce FLUXSynID, a framework for generating high-resolution synthetic face datasets along with a dataset of 14,889 synthetic identities. We generate synthetic faces with user-defined identity attribute distributions, offering both document-style and trusted live capture images. The dataset generated using the FLUXSynID framework shows improved alignment with real-world identity distributions and greater inter-class diversity compared to prior work. Our work is publicly released to support biometric research, including face recognition and morphing attack detection.

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