mlsanityData to 14 Oct 2026

Face Recognition: Too Bias, or Not Too Bias?

arXiv 2002.06483 ↗First posted 16 Feb 2020cs.CVcited by 82

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Abstract (arXiv)

We reveal critical insights into problems of bias in state-of-the-art facial recognition (FR) systems using a novel Balanced Faces In the Wild (BFW) dataset: data balanced for gender and ethnic groups. We show variations in the optimal scoring threshold for face-pairs across different subgroups. Thus, the conventional approach of learning a global threshold for all pairs resulting in performance gaps among subgroups. By learning subgroup-specific thresholds, we not only mitigate problems in performance gaps but also show a notable boost in the overall performance. Furthermore, we do a human evaluation to measure the bias in humans, which supports the hypothesis that such a bias exists in human perception. For the BFW database, source code, and more, visit github.com/visionjo/facerec-bias-bfw.

Key facts. Cited by 82 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Feb 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 22; 2022: 13; 2023: 15; 2024: 15; 2025: 12; 2026: 5.

82 papers.

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  1. 2021A Comprehensive Study on Face Recognition Biases Beyond Demographicscited by 86
  2. 2021A Survey on Bias in Visual Datasetscited by 84
  3. 2021Understanding and Mitigating Annotation Bias in Facial Expression Recognitioncited by 50
  4. 2021Consistent Instance False Positive Improves Fairness in Face Recognitioncited by 40
  5. 2021PASS: Protected Attribute Suppression System for Mitigating Bias in Face Recognitioncited by 38
  6. 2021One Label, One Billion Faces: Usage and Consistency of Racial Categories in Computer Visioncited by 33
  7. 2023Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitmentcited by 33
  8. 2021Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimizationcited by 32
  9. 2022Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguationcited by 32
  10. 2021Pre-training strategies and datasets for facial representation learningcited by 26
  11. 2021Deepfake Videos in the Wild: Analysis and Detectioncited by 23
  12. 2021Domain-Incremental Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognitioncited by 19
38 more
  1. 2021Anatomizing Bias in Facial Analysiscited by 18
  2. 2021Balancing Biases and Preserving Privacy on Balanced Faces in the Wildcited by 17
  3. 2021FairCal: Fairness Calibration for Face Verificationcited by 17
  4. 2021Multiset-Equivariant Set Prediction with Approximate Implicit Differentiationcited by 17
  5. 2023Ethical Considerations for Responsible Data Curationcited by 17
  6. 2021Measuring Hidden Bias within Face Recognition via Racial Phenotypescited by 16
  7. 202550 Years of Automated Face Recognitioncited by 15
  8. 2023Towards Fair Face Verification: An In-depth Analysis of Demographic Biasescited by 14
  9. 2022A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairnesscited by 13
  10. 2023What Should Be Balanced in a "Balanced" Face Recognition Dataset?cited by 13
  11. 2022Mitigating Gender Bias in Face Recognition Using the von Mises-Fisher Mixture Modelcited by 12
  12. 2025Face-Human-Bench: A Comprehensive Benchmark of Face and Human Understanding for Multi-modal Assistantscited by 12
  13. 2022A Deep Dive into Dataset Imbalance and Bias in Face Identificationcited by 11
  14. 2023Bias and Diversity in Synthetic-based Face Recognitioncited by 11
  15. 2022How to Boost Face Recognition with StyleGAN?cited by 10
  16. 2023Fairness in Visual Clustering: A Novel Transformer Clustering Approachcited by 10
  17. 2024Synthetic Data for the Mitigation of Demographic Biases in Face Recognitioncited by 10
  18. 2023Racial Bias within Face Recognition: A Surveycited by 9
  19. 2024Thinking Racial Bias in Fair Forgery Detection: Models, Datasets and Evaluationscited by 8
  20. 2021Hierarchical Attention-based Age Estimation and Bias Estimationcited by 7
  21. 2022Towards Explaining Demographic Bias through the Eyes of Face Recognition Modelscited by 7
  22. 2022The Impact of Racial Distribution in Training Data on Face Recognition Bias: A Closer Lookcited by 7
  23. 2023Gradient Attention Balance Network: Mitigating Face Recognition Racial Bias via Gradient Attentioncited by 7
  24. 2025Review of Demographic Fairness in Face Recognitioncited by 7
  25. 2021Distill and De-bias: Mitigating Bias in Face Verification using Knowledge Distillationcited by 6
  26. 2022CAT: Controllable Attribute Translation for Fair Facial Attribute Classificationcited by 6
  27. 2023A View From Somewhere: Human-Centric Face Representationscited by 6
  28. 2023Invariant Feature Regularization for Fair Face Recognitioncited by 6
  29. 2021Face Verification with Challenging Imposters and Diversified Demographicscited by 5
  30. 2021Algorithmic Fairness in Face Morphing Attack Detectioncited by 5
  31. 2022Assessing Bias in Face Image Quality Assessmentcited by 5
  32. 2023Optimization-Based Improvement of Face Image Quality Assessment Techniquescited by 5
  33. 2024Model Compression Techniques in Biometrics Applications: A Surveycited by 5
  34. 2024Can the accuracy bias by facial hairstyle be reduced through balancing the training data?cited by 5
  35. 2021Learning Fair Face Representation With Progressive Cross Transformercited by 4
  36. 2021The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Facescited by 4
  37. 2023Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representationscited by 4
  38. 2024Lookism: The overlooked bias in computer visioncited by 4

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