Private Face Recognition Training Dataset Publication via Identity-Decoupled and Geometry-Preserving Face Distillation
Private Face Distillation is proposed, an identity-decoupling and geometry-preserving framework that uses Orthogonal Geometry Preservation to construct decoupled proxy identities from private identity representations while maintaining hyperspherical geometry, and Relational Topology Alignment to preserve identity relations for recognition learning.