A KAN-based mapping network can translate embeddings from privacy-preserving face recognition systems into the input space of a face diffusion model, enabling face reconstruction attacks with high attack success rates.
Besides, we use default training configurations for PartialFace implementation (Mi et al., 2023)9, 27 random sub channels are selecting for training
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KAN See Your Face
A KAN-based mapping network can translate embeddings from privacy-preserving face recognition systems into the input space of a face diffusion model, enabling face reconstruction attacks with high attack success rates.