Summary of Difffinger: Advancing Synthetic Fingerprint Generation Through Denoising Diffusion Probabilistic Models, by Freddie Grabovski et al.
DiffFinger: Advancing Synthetic Fingerprint Generation through Denoising Diffusion Probabilistic Models
by Freddie Grabovski, Lior Yasur, Yaniv Hacmon, Lior Nisimov, Stav Nimrod
First submitted to arxiv on: 15 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty summary: This paper presents an innovative approach for generating synthesized fingerprint images using Denoising Diffusion Probabilistic Models (DDPMs). By leveraging DDPMs, researchers aim to overcome the limitations of Generative Adversarial Networks (GANs) in producing realistic fingerprint images. The proposed method showcases increased clarity and realism while maintaining diversity, outperforming authentic training set data in quality. Moreover, it provides a richer set of biometric data, reflecting true-to-life variability. This breakthrough paves the way for advancing fingerprint identification and authentication systems. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty summary: Scientists are working on creating fake fingerprints that look real using special computer models called Denoising Diffusion Probabilistic Models (DDPMs). They want to make better fake biometric data, like fingerprints, because it’s hard to get good real data without invading people’s privacy. The researchers use DDPMs to generate fake fingerprints that are both clear and varied. Their results show that these fake fingerprints are just as good as real ones and can even provide more variety. This breakthrough could help improve fingerprint recognition systems. |
Keywords
» Artificial intelligence » Diffusion
