Zero-Shot Generative De-identification: Inversion-Free Flow for Privacy-Preserving Skin Image Analysis

ArXi:2602.00821v2 Announce Type: replace The secure analysis of dermatological images in clinical environments is fundamentally restricted by the critical trade-off between patient privacy and the preservation of diagnostic fidelity. Traditional de-identification techniques often degrade essential pathological markers, while state-of-the-art generative approaches typically require computationally intensive inversion processes or extensive task-specific fine-tuning, limiting their feasibility for real-time deployment. This study.