mlsanityData to 14 Oct 2026

Privacy-Preserving Face Recognition Using Trainable Feature Subtraction

arXiv 2403.12457 ↗First posted 19 Mar 2024cs.CVcited by 24

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Abstract (arXiv)

The widespread adoption of face recognition has led to increasing privacy concerns, as unauthorized access to face images can expose sensitive personal information. This paper explores face image protection against viewing and recovery attacks. Inspired by image compression, we propose creating a visually uninformative face image through feature subtraction between an original face and its model-produced regeneration. Recognizable identity features within the image are encouraged by co-training a recognition model on its high-dimensional feature representation. To enhance privacy, the high-dimensional representation is crafted through random channel shuffling, resulting in randomized recognizable images devoid of attacker-leverageable texture details. We distill our methodologies into a novel privacy-preserving face recognition method, MinusFace. Experiments demonstrate its high recognition accuracy and effective privacy protection. Its code is available at https://github.com/Tencent/TFace.

Key facts. Cited by 24 papers in the map (data through 14 Oct 2026). Builds on 29 of its 69 references that are in the map. First posted on arXiv 19 Mar 2024.

Builds on

29 of 69 references.

References · 29

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2018CosFace: Large Margin Cosine Loss for Deep Face Recognitioncited by 971
  4. 2017SphereFace: Deep Hypersphere Embedding for Face Recognitioncited by 737
  5. 2016MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognitioncited by 624
  6. 2020CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognitioncited by 321
  7. 2017Lossy Image Compression with Compressive Autoencoderscited by 294
  8. 2018Deep Face Recognition: A Surveycited by 276
  9. 2017Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environmentscited by 260
  10. 2020Learning in the Frequency Domaincited by 198
  11. 2023FreeU: Free Lunch in Diffusion U-Netcited by 196
  12. 2015Inverting Visual Representations with Convolutional Networkscited by 170
17 more
  1. 2019Mitigate Bias in Face Recognition using Skewness-Aware Reinforcement Learningcited by 145
  2. 2023Collaborative Diffusion for Multi-Modal Face Generation and Editingcited by 116
  3. 2020InstaHide: Instance-hiding Schemes for Private Distributed Learningcited by 90
  4. 2023IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Modelscited by 72
  5. 2017On the Reconstruction of Face Images from Deep Face Templatescited by 67
  6. 2022SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Datacited by 63
  7. 2020Privacy Preserving Face Recognition Utilizing Differential Privacycited by 30
  8. 2022Privacy-Preserving Face Recognition with Learnable Privacy Budgets in Frequency Domaincited by 28
  9. 2021IdentityDP: Differential Private Identification Protection for Face Imagescited by 24
  10. 2023Privacy-preserving Adversarial Facial Featurescited by 24
  11. 2023TransFace++: Rethinking the Face Recognition Paradigm with a Focus on Accuracy, Efficiency, and Securitycited by 22
  12. 2017Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Imagescited by 20
  13. 2022DuetFace: Collaborative Privacy-Preserving Face Recognition via Channel Splitting in the Frequency Domaincited by 18
  14. 2022An Overview of Privacy-enhancing Technologies in Biometric Recognitioncited by 17
  15. 2023Privacy-Preserving Face Recognition Using Random Frequency Componentscited by 15
  16. 2023Improving Adversarial Robustness of Masked Autoencoders via Test-time Frequency-domain Promptingcited by 12
  17. 2018Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding Arbitrary Gender Classifierscited by 10

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 7; 2026: 11.

24 papers.

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  1. 2024Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuningcited by 59
  2. 2025HunyuanPortrait: Implicit Condition Control for Enhanced Portrait Animationcited by 59
  3. 2025Data Synthesis with Diverse Styles for Face Recognition via 3DMM-Guided Diffusioncited by 12
  4. 2024SlerpFace: Face Template Protection via Spherical Linear Interpolationcited by 8
  5. 2025Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference Systemscited by 6
  6. 2025BlurDM: A Blur Diffusion Model for Image Deblurringcited by 5
  7. 2025IDFace: Face Template Protection for Efficient and Secure Identificationcited by 3
  8. 2024PixelFade: Privacy-preserving Person Re-identification with Noise-guided Progressive Replacementcited by 2
  9. 2024FaceTracer: Unveiling Source Identities from Swapped Face Images and Videos for Fraud Preventioncited by 2
  10. 2025CryptoFace: End-to-End Encrypted Face Recognitioncited by 2
  11. 2026LDP-Slicing: Local Differential Privacy for Images via Randomized Bit-Plane Slicingcited by 2
  12. 2024Facial Expression Recognition with Controlled Privacy Preservation and Feature Compensationcited by 1
12 more
  1. 2025ImmerIris: A Large-Scale Dataset and Benchmark for Off-Axis and Unconstrained Iris Recognition in Immersive Applicationscited by 1
  2. 2026Adv-TGD: Adversarial Text-Guided Diffusion for Face Recognition Impersonation Attackscited by 1
  3. 2026HNDiff: Haze-Noise Diffusion for Image Dehazingcited by 1
  4. 2024RDP: Ranked Differential Privacy for Facial Feature Protection in Multiscale Sparsified Subspacecited by 0
  5. 2026FaceLinkGen: A Re-evaluation of Identity Leakage in Privacy-Preserving Face Recognition and Face Anonymization Systems Using Simple Distillationcited by 0
  6. 2026Realistic Face Reconstruction from Facial Embeddings via Diffusion Modelscited by 0
  7. 2026EventFace: Event-Based Face Recognition via Structure-Driven Spatiotemporal Modelingcited by 0
  8. 2026SteerFace: Debiasing Synthetic Face Generation via Adaptive Residue Perturbationcited by 0
  9. 2026DecoyFace: Beyond Obfuscation via Controllable and Imperceptible Identity Misdirection for Privacy-Preserving Face Recognitioncited by 0
  10. 2026Face De-Identification: A Domain-Centric Survey from Capture to Processingcited by 0
  11. 2026Private Face Recognition Training Dataset Publication via Identity-Decoupled and Geometry-Preserving Face Distillationcited by 0
  12. 2026DiffAttack: Evasion Attacks Against Face Recognition via Latent Diffusion Modelscited by 0