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Chalearn LAP In-painting Competition Track 3 - Fingerprint Denoising and In-painting

The dataset provided by the organizers consisted of 84000 (200, 400) fingerprint images generated using Anguli: Synthetic Fingerprint Generator. Those images were then artificially degraded by adding a background and random transformations (blur, brightness, contrast, elastic transformation, occlusion, scratch, resolution, rotation).

Data and Resources

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Cite this as

Youness MANSAR (2024). Dataset: Chalearn LAP In-painting Competition Track 3 - Fingerprint Denoising and In-painting. https://doi.org/10.57702/g313sbd5

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It is available for use in manuscripts, and will be published when the Dataset is made public.

Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Author	Youness MANSAR
Homepage	https://github.com/CVxTz/fingerprint_denoising