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Generating Photo-Realistic Training Data to Improve Face Recognition Accuracy

Face datasets are widely used in face recognition tasks, but they are often limited by their size and quality. This paper proposes a method for generating photo-realistic synthetic images of faces to augment existing face datasets.

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Cite this as

Daniel S´aez Trigueros, Li Meng, Margaret Hartnett (2024). Dataset: Generating Photo-Realistic Training Data to Improve Face Recognition Accuracy. https://doi.org/10.57702/x9wnpvra

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Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Defined In	https://doi.org/10.48550/arXiv.1811.00112
Author	Daniel S´aez Trigueros
More Authors	Li Meng Margaret Hartnett
Homepage	https://arxiv.org/abs/1806.08906