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Found 2 papers, 2 papers with code
Identity-driven Three-Player Generative Adversarial Network for Synthetic-based Face Recognition
We empirically proved that our IDnet synthetic images are of higher identity discrimination in comparison to the conventional two-player GAN, while maintaining a realistic intra-identity variation.
SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data
The reported evaluation results on five authentic face benchmarks demonstrated that the privacy-friendly synthetic dataset has high potential to be used for training face recognition models, achieving, for example, a verification accuracy of 91. 87\% on LFW using multi-class classification and 99. 13\% using the combined learning strategy.
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