Summary of Genpalm: Contactless Palmprint Generation with Diffusion Models, by Steven A. Grosz and Anil K. Jain
GenPalm: Contactless Palmprint Generation with Diffusion Models
by Steven A. Grosz, Anil K. Jain
First submitted to arxiv on: 1 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 The paper proposes a novel method for synthesizing palmprint images using diffusion probabilistic models, addressing the scarcity of large-scale palmprint databases. This end-to-end framework generates multiple palm identities, enhancing contactless palmprint recognition performance across various test databases. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research creates fake palmprint pictures to help people recognize palms without touching them. It uses special computer programs called diffusion probabilistic models to make these pictures more realistic and useful. The paper shows that its method can improve how well computers recognize palms, even when using old or new pictures from different places. |
Keywords
» Artificial intelligence » Diffusion » Palm
