mlsanityData to 14 Oct 2026

Biometrics: Trust, but Verify

arXiv 2105.06625 ↗First posted 14 May 2021cs.CVcited by 39

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Abstract (arXiv)

Over the past two decades, biometric recognition has exploded into a plethora of different applications around the globe. This proliferation can be attributed to the high levels of authentication accuracy and user convenience that biometric recognition systems afford end-users. However, in-spite of the success of biometric recognition systems, there are a number of outstanding problems and concerns pertaining to the various sub-modules of biometric recognition systems that create an element of mistrust in their use - both by the scientific community and also the public at large. Some of these problems include: i) questions related to system recognition performance, ii) security (spoof attacks, adversarial attacks, template reconstruction attacks and demographic information leakage), iii) uncertainty over the bias and fairness of the systems to all users, iv) explainability of the seemingly black-box decisions made by most recognition systems, and v) concerns over data centralization and user privacy. In this paper, we provide an overview of each of the aforementioned open-ended challenges. We survey work that has been conducted to address each of these concerns and highlight the issues requiring further attention. Finally, we provide insights into how the biometric community can address core biometric recognition systems design issues to better instill trust, fairness, and security for all.

Key facts. Cited by 39 papers in the map (data through 14 Oct 2026). Builds on 118 of its 276 references that are in the map. First posted on arXiv 14 May 2021.

Builds on

118 of 276 references.

References · 118

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38 more
  1. 2018CosFace: Large Margin Cosine Loss for Deep Face Recognitioncited by 971
  2. 2016Adversarial Machine Learning at Scalecited by 936
  3. 2018Robustness May Be at Odds with Accuracycited by 880
  4. 2016MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognitioncited by 624
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50 most cited of 118 All 118 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 3; 2022: 13; 2023: 9; 2024: 7; 2025: 6; 2026: 1.

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  1. 2022A Comprehensive Survey on Deep Gait Recognition: Algorithms, Datasets and Challengescited by 45
  2. 2023L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learningcited by 30
  3. 2022Synthetic Data in Human Analysis: A Surveycited by 28
  4. 2022Deep Learning for Iris Recognition: A Surveycited by 25
  5. 2022edBB-Demo: Biometrics and Behavior Analysis for Online Educational Platformscited by 18
  6. 2022An Overview of Privacy-enhancing Technologies in Biometric Recognitioncited by 17
  7. 2022Federated Self-supervised Learning for Video Understandingcited by 13
  8. 2021Demographic Fairness in Biometric Systems: What do the Experts say?cited by 12
  9. 2023Efficient Explainable Face Verification based on Similarity Score Argument Backpropagationcited by 12
  10. 2024Open-Set Biometrics: Beyond Good Closed-Set Modelscited by 12
  11. 2022The Value of AI Guidance in Human Examination of Synthetically-Generated Facescited by 8
  12. 20233D Face Reconstruction: the Road to Forensicscited by 7
27 more
  1. 2025Review of Demographic Fairness in Face Recognitioncited by 7
  2. 2021Semantic Segmentation of Periocular Near-Infra-Red Eye Images Under Alcohol Effectscited by 6
  3. 2022Haven't I Seen You Before? Assessing Identity Leakage in Synthetic Irisescited by 6
  4. 2024Privacy-Safe Iris Presentation Attack Detectioncited by 6
  5. 2022Dictionary Attacks on Speaker Verificationcited by 5
  6. 2023M3FAS: An Accurate and Robust MultiModal Mobile Face Anti-Spoofing Systemcited by 5
  7. 2024Can the accuracy bias by facial hairstyle be reduced through balancing the training data?cited by 5
  8. 2025Deep Learning in Palmprint Recognition-A Comprehensive Surveycited by 5
  9. 20233D Face Reconstruction for Forensic Recognition -- A Surveycited by 4
  10. 2023Joint Person Identity, Gender and Age Estimation from Hand Images using Deep Multi-Task Representation Learningcited by 4
  11. 2023An Explainable Model-Agnostic Algorithm for CNN-based Biometrics Verificationcited by 4
  12. 2026LocalScore: Local Density-Aware Similarity Scoring for Biometricscited by 4
  13. 2022Local-Aware Global Attention Network for Person Re-Identification Based on Body and Hand Imagescited by 3
  14. 2022Deep representation learning: Fundamentals, Perspectives, Applications, and Open Challengescited by 3
  15. 2024Beyond Spatial Explanations: Explainable Face Recognition in the Frequency Domaincited by 3
  16. 2022On Demographic Bias in Fingerprint Recognitioncited by 2
  17. 2024LabellessFace: Fair Metric Learning for Face Recognition without Attribute Labelscited by 2
  18. 2025ColFigPhotoAttnNet: Reliable Finger Photo Presentation Attack Detection Leveraging Window-Attention on Color Spacescited by 2
  19. 2022Learning to Predict Fitness for Duty using Near Infrared Periocular Iris Imagescited by 1
  20. 2023Fitness-for-Duty Classification using Temporal Sequences of Iris Periocular imagescited by 1
  21. 2021DFCANet: Dense Feature Calibration-Attention Guided Network for Cross Domain Iris Presentation Attack Detectioncited by 0
  22. 2023Introduction to Presentation Attack Detection in Fingerprint Biometricscited by 0
  23. 2024Explainable offline automatic signature verifier to support forensic handwriting examinerscited by 0
  24. 2024Unsupervised Fingerphoto Presentation Attack Detection With Diffusion Modelscited by 0
  25. 2025An Investigation of Ear-EEG Signals for a Novel Biometric Authentication Systemcited by 0
  26. 2025Deceptive Beauty: Evaluating the Impact of Beauty Filters on Deepfake and Morphing Attack Detectioncited by 0
  27. 2025Mitigating Bias with Words: Inducing Demographic Ambiguity in Face Recognition Templates by Text Encodingcited by 0