FairFaceGen

The FairFaceGen is a dataset of synthetic faces generated to study the impact of synthetic data generation on the performance and bias of face recognition (FR) models. It has about 11+11=22K identities and is built using prompt-based balanced generation across age, race, and gender attributes using Flux.1-dev and Stable Diffusion v3.5 generators. The identity variations are generated using Arc2Face and IP-Adapter variants (SD15 and SDXL backbones, with FaceID/CLIP embeddings) generators that produce variations per identity.