SteerFace: Debiasing Synthetic Face Generation via Adaptive Residue Perturbation 事件

SteerFace: Debiasing Synthetic Face Generation via Adaptive Residue Perturbation arXiv:2605.30894v1 Announce Type: new Abstract: The shortage of legally compliant data for face recognition training has sparked growing interest in using synthetic data as an alternative. While recent diffusion-based methods enable the generation of photorealistic face images with strong identity adherence and data diversity, their downstream recognition performance still exhibits a significant synthetic-real gap.