AI RESEARCH
Intra-finger Variability of Diffusion-based Latent Fingerprint Generation
arXiv CS.CV
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ArXi:2604.10040v1 Announce Type: new The primary goal of this work is to systematically evaluate the intra-finger variability of synthetic fingerprints (particularly latent prints) generated using a state-of-the-art diffusion model. Specifically, we focus on enhancing the latent style diversity of the generative model by constructing a comprehensive \textit{latent style bank} curated from seven diverse datasets, which enables the precise synthesis of latent prints with over 40 distinct styles encapsulating different surfaces and processing techniques.