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.

Data and Resources

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

DOI retrieved: December 3, 2024

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