{"total":80,"rows":[{"id":"2103.01592","title":"A Comprehensive Study on Face Recognition Biases Beyond Demographics","created":"2021-03-02","cited_by_count":86,"area":null},{"id":"2107.07919","title":"A Survey on Bias in Visual Datasets","created":"2021-07-16","cited_by_count":84,"area":null},{"id":"2108.08504","title":"Understanding and Mitigating Annotation Bias in Facial Expression Recognition","created":"2021-08-19","cited_by_count":50,"area":null},{"id":"2106.05519","title":"Consistent Instance False Positive Improves Fairness in Face Recognition","created":"2021-06-10","cited_by_count":40,"area":null},{"id":"2108.03764","title":"PASS: Protected Attribute Suppression System for Mitigating Bias in Face Recognition","created":"2021-08-09","cited_by_count":38,"area":null},{"id":"2102.02320","title":"One Label, One Billion Faces: Usage and Consistency of Racial Categories in Computer Vision","created":"2021-02-03","cited_by_count":33,"area":null},{"id":"2302.10908","title":"Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment","created":"2023-02-13","cited_by_count":33,"area":null},{"id":"2108.05449","title":"Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization","created":"2021-08-11","cited_by_count":32,"area":null},{"id":"2205.03962","title":"Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation","created":"2022-05-08","cited_by_count":32,"area":null},{"id":"2103.16554","title":"Pre-training strategies and datasets for facial representation learning","created":"2021-03-30","cited_by_count":26,"area":null},{"id":"2103.04263","title":"Deepfake Videos in the Wild: Analysis and Detection","created":"2021-03-07","cited_by_count":23,"area":null},{"id":"2103.08637","title":"Domain-Incremental Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition","created":"2021-03-15","cited_by_count":19,"area":null},{"id":"2112.06522","title":"Anatomizing Bias in Facial Analysis","created":"2021-12-13","cited_by_count":18,"area":null},{"id":"2103.09118","title":"Balancing Biases and Preserving Privacy on Balanced Faces in the Wild","created":"2021-03-16","cited_by_count":17,"area":null},{"id":"2106.03761","title":"FairCal: Fairness Calibration for Face Verification","created":"2021-06-07","cited_by_count":17,"area":null},{"id":"2111.12193","title":"Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation","created":"2021-11-23","cited_by_count":17,"area":null},{"id":"2302.03629","title":"Ethical Considerations for Responsible Data Curation","created":"2023-02-07","cited_by_count":17,"area":null},{"id":"2110.09839","title":"Measuring Hidden Bias within Face Recognition via Racial Phenotypes","created":"2021-10-19","cited_by_count":16,"area":null},{"id":"2505.24247","title":"50 Years of Automated Face Recognition","created":"2025-05-30","cited_by_count":15,"area":null},{"id":"2307.10011","title":"Towards Fair Face Verification: An In-depth Analysis of Demographic Biases","created":"2023-07-19","cited_by_count":14,"area":null},{"id":"2212.09006","title":"A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness","created":"2022-12-18","cited_by_count":13,"area":null},{"id":"2304.09818","title":"What Should Be Balanced in a \"Balanced\" Face Recognition Dataset?","created":"2023-04-17","cited_by_count":13,"area":null},{"id":"2210.13664","title":"Mitigating Gender Bias in Face Recognition Using the von Mises-Fisher Mixture Model","created":"2022-10-24","cited_by_count":12,"area":null},{"id":"2501.01243","title":"Face-Human-Bench: A Comprehensive Benchmark of Face and Human Understanding for Multi-modal Assistants","created":"2025-01-02","cited_by_count":12,"area":null},{"id":"2203.08235","title":"A Deep Dive into Dataset Imbalance and Bias in Face Identification","created":"2022-03-15","cited_by_count":11,"area":null},{"id":"2311.03970","title":"Bias and Diversity in Synthetic-based Face Recognition","created":"2023-11-07","cited_by_count":11,"area":null},{"id":"2210.10090","title":"How to Boost Face Recognition with StyleGAN?","created":"2022-10-18","cited_by_count":10,"area":null},{"id":"2304.07408","title":"Fairness in Visual Clustering: A Novel Transformer Clustering Approach","created":"2023-04-14","cited_by_count":10,"area":null},{"id":"2402.01472","title":"Synthetic Data for the Mitigation of Demographic Biases in Face Recognition","created":"2024-02-02","cited_by_count":10,"area":null},{"id":"2305.00817","title":"Racial Bias within Face Recognition: A Survey","created":"2023-05-01","cited_by_count":9,"area":null},{"id":"2407.14367","title":"Thinking Racial Bias in Fair Forgery Detection: Models, Datasets and Evaluations","created":"2024-07-19","cited_by_count":8,"area":null},{"id":"2103.09882","title":"Hierarchical Attention-based Age Estimation and Bias Estimation","created":"2021-03-17","cited_by_count":7,"area":null},{"id":"2208.13400","title":"Towards Explaining Demographic Bias through the Eyes of Face Recognition Models","created":"2022-08-29","cited_by_count":7,"area":null},{"id":"2211.14498","title":"The Impact of Racial Distribution in Training Data on Face Recognition Bias: A Closer Look","created":"2022-11-26","cited_by_count":7,"area":null},{"id":"2304.02284","title":"Gradient Attention Balance Network: Mitigating Face Recognition Racial Bias via Gradient Attention","created":"2023-04-05","cited_by_count":7,"area":null},{"id":"2502.02309","title":"Review of Demographic Fairness in Face Recognition","created":"2025-02-04","cited_by_count":7,"area":null},{"id":"2209.06850","title":"CAT: Controllable Attribute Translation for Fair Facial Attribute Classification","created":"2022-09-14","cited_by_count":6,"area":null},{"id":"2303.17176","title":"A View From Somewhere: Human-Centric Face Representations","created":"2023-03-30","cited_by_count":6,"area":null},{"id":"2310.14652","title":"Invariant Feature Regularization for Fair Face Recognition","created":"2023-10-23","cited_by_count":6,"area":null},{"id":"2110.08667","title":"Face Verification with Challenging Imposters and Diversified Demographics","created":"2021-10-16","cited_by_count":5,"area":null},{"id":"2111.12115","title":"Algorithmic Fairness in Face Morphing Attack Detection","created":"2021-11-23","cited_by_count":5,"area":null},{"id":"2211.15265","title":"Assessing Bias in Face Image Quality Assessment","created":"2022-11-28","cited_by_count":5,"area":null},{"id":"2305.14856","title":"Optimization-Based Improvement of Face Image Quality Assessment Techniques","created":"2023-05-24","cited_by_count":5,"area":null},{"id":"2401.10139","title":"Model Compression Techniques in Biometrics Applications: A Survey","created":"2024-01-18","cited_by_count":5,"area":null},{"id":"2405.20062","title":"Can the accuracy bias by facial hairstyle be reduced through balancing the training data?","created":"2024-05-30","cited_by_count":5,"area":null},{"id":"2108.04983","title":"Learning Fair Face Representation With Progressive Cross Transformer","created":"2021-08-11","cited_by_count":4,"area":null},{"id":"2111.00598","title":"The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Faces","created":"2021-10-31","cited_by_count":4,"area":null},{"id":"2311.18575","title":"Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations","created":"2023-11-30","cited_by_count":4,"area":null},{"id":"2408.11448","title":"Lookism: The overlooked bias in computer vision","created":"2024-08-21","cited_by_count":4,"area":null},{"id":"2409.12318","title":"A large-scale study of performance and equity of commercial remote identity verification technologies across demographics","created":"2024-09-18","cited_by_count":4,"area":null},{"id":"2211.03588","title":"Are Face Detection Models Biased?","created":"2022-11-07","cited_by_count":3,"area":null},{"id":"2211.03705","title":"A Survey on Computer Vision based Human Analysis in the COVID-19 Era","created":"2022-11-07","cited_by_count":3,"area":null},{"id":"2301.05776","title":"Young Labeled Faces in the Wild (YLFW): A Dataset for Children Faces Recognition","created":"2023-01-13","cited_by_count":3,"area":null},{"id":"2405.09403","title":"Identity Overlap Between Face Recognition Train/Test Data: Causing Optimistic Bias in Accuracy Measurement","created":"2024-05-15","cited_by_count":3,"area":null},{"id":"2407.11941","title":"Beyond Spatial Explanations: Explainable Face Recognition in the Frequency Domain","created":"2024-07-16","cited_by_count":3,"area":null},{"id":"2408.10175","title":"Fairness Under Cover: Evaluating the Impact of Occlusions on Demographic Bias in Facial Recognition","created":"2024-08-19","cited_by_count":3,"area":null},{"id":"2202.10943","title":"Gradient Based Activations for Accurate Bias-Free Learning","created":"2022-02-17","cited_by_count":2,"area":null},{"id":"2310.15848","title":"On Responsible Machine Learning Datasets with Fairness, Privacy, and Regulatory Norms","created":"2023-10-24","cited_by_count":2,"area":null},{"id":"2412.03349","title":"Fairer Analysis and Demographically Balanced Face Generation for Fairer Face Verification","created":"2024-12-04","cited_by_count":2,"area":null},{"id":"2510.15520","title":"Discovering Intersectional Bias via Directional Alignment in Face Recognition Embeddings","created":"2025-10-17","cited_by_count":2,"area":null},{"id":"2111.00660","title":"Evaluation of Human and Machine Face Detection using a Novel Distinctive Human Appearance Dataset","created":"2021-11-01","cited_by_count":1,"area":null},{"id":"2208.13061","title":"On Biased Behavior of GANs for Face Verification","created":"2022-08-27","cited_by_count":1,"area":null},{"id":"2404.15385","title":"Sum of Group Error Differences: A Critical Examination of Bias Evaluation in Biometric Verification and a Dual-Metric Measure","created":"2024-04-23","cited_by_count":1,"area":null},{"id":"2507.17192","title":"Vec2Face+ for Face Dataset Generation","created":"2025-07-23","cited_by_count":1,"area":null},{"id":"2305.00352","title":"Embedding Aggregation for Forensic Facial Comparison","created":"2023-04-29","cited_by_count":0,"area":null},{"id":"2402.13771","title":"Mask-up: Investigating Biases in Face Re-identification for Masked Faces","created":"2024-02-21","cited_by_count":0,"area":null},{"id":"2404.09703","title":"AI Competitions and Benchmarks: Dataset Development","created":"2024-04-15","cited_by_count":0,"area":null},{"id":"2406.16592","title":"Toward Fairer Face Recognition Datasets","created":"2024-06-24","cited_by_count":0,"area":null},{"id":"2502.04391","title":"Towards Fair and Robust Face Parsing for Generative AI: A Multi-Objective Approach","created":"2025-02-06","cited_by_count":0,"area":null},{"id":"2502.11031","title":"A Critical Review of Predominant Bias in Neural Networks","created":"2025-02-16","cited_by_count":0,"area":null},{"id":"2504.19370","title":"Mitigating Bias in Facial Recognition Systems: Centroid Fairness Loss Optimization","created":"2025-04-27","cited_by_count":0,"area":null},{"id":"2505.01699","title":"Component-Based Fairness in Face Attribute Classification with Bayesian Network-informed Meta Learning","created":"2025-05-03","cited_by_count":0,"area":null},{"id":"2506.01532","title":"Balancing Beyond Discrete Categories: Continuous Demographic Labels for Fair Face Recognition","created":"2025-06-02","cited_by_count":0,"area":null},{"id":"2510.20482","title":"Reliable and Reproducible Demographic Inference for Fairness in Face Analysis","created":"2025-10-23","cited_by_count":0,"area":null},{"id":"2512.08981","title":"Mitigating Bias with Words: Inducing Demographic Ambiguity in Face Recognition Templates by Text Encoding","created":"2025-12-05","cited_by_count":0,"area":null},{"id":"2604.10014","title":"Demographic and Linguistic Bias Evaluation in Omnimodal Language Models","created":"2026-04-11","cited_by_count":0,"area":null},{"id":"2605.15312","title":"Beyond Performance Disparities: A Three-Level Audit of Representational Harm in CelebA","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2606.04469","title":"Adaptive Calibration for Fair and Performant Facial Recognition","created":"2026-06-03","cited_by_count":0,"area":null},{"id":"2608.12971","title":"Bias Mitigation in Face Recognition via Demographic-based Supervised Contrastive Learning","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2608.30688","title":"UFPR-PEs: A Brazilian Face Recognition Benchmark with Self-Declared Race/Color Labels","created":"2026-08-31","cited_by_count":0,"area":null}],"next_cursor":null}