mlsanityData to 7 Oct 2026

Data Uncertainty Learning in Face Recognition

arXiv 2003.11339 ↗First posted 25 Mar 2020cs.CVcited by 134

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Abstract (arXiv)

Modeling data uncertainty is important for noisy images, but seldom explored for face recognition. The pioneer work, PFE, considers uncertainty by modeling each face image embedding as a Gaussian distribution. It is quite effective. However, it uses fixed feature (mean of the Gaussian) from an existing model. It only estimates the variance and relies on an ad-hoc and costly metric. Thus, it is not easy to use. It is unclear how uncertainty affects feature learning. This work applies data uncertainty learning to face recognition, such that the feature (mean) and uncertainty (variance) are learnt simultaneously, for the first time. Two learning methods are proposed. They are easy to use and outperform existing deterministic methods as well as PFE on challenging unconstrained scenarios. We also provide insightful analysis on how incorporating uncertainty estimation helps reducing the adverse effects of noisy samples and affects the feature learning.

Key facts. Cited by 134 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Mar 2020.

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Citing papers per year: 2021: 22; 2022: 35; 2023: 35; 2024: 19; 2025: 18; 2026: 5.

134 papers.

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  1. 2022AdaFace: Quality Adaptive Margin for Face Recognitioncited by 390
  2. 2021MagFace: A Universal Representation for Face Recognition and Quality Assessmentcited by 332
  3. 2021Probabilistic Embeddings for Cross-Modal Retrievalcited by 150
  4. 2022Uncertainty Modeling for Out-of-Distribution Generalizationcited by 122
  5. 2021Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognitioncited by 89
  6. 2023Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detectioncited by 88
  7. 2023A Survey on Uncertainty Quantification Methods for Deep Learningcited by 78
  8. 2022Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FCcited by 73
  9. 2021Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regressioncited by 58
  10. 2023UATVR: Uncertainty-Adaptive Text-Video Retrievalcited by 55
  11. 2022Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularizationcited by 45
  12. 2023Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streakscited by 45
38 more
  1. 2021von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learningcited by 42
  2. 2022MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Modelcited by 41
  3. 2023Improved Probabilistic Image-Text Representationscited by 40
  4. 2021Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generationcited by 35
  5. 2022Probabilistic Representations for Video Contrastive Learningcited by 33
  6. 2023RTMO: Towards High-Performance One-Stage Real-Time Multi-Person Pose Estimationcited by 33
  7. 2024ExACT: Language-guided Conceptual Reasoning and Uncertainty Estimation for Event-based Action Recognition and Morecited by 33
  8. 2022Uncertainty-Aware Multi-View Representation Learningcited by 29
  9. 2022PMAL: Open Set Recognition via Robust Prototype Miningcited by 27
  10. 2023The Treasure Beneath Multiple Annotations: An Uncertainty-aware Edge Detectorcited by 25
  11. 2021T-SVDNet: Exploring High-Order Prototypical Correlations for Multi-Source Domain Adaptationcited by 24
  12. 2022COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognitioncited by 22
  13. 2022Controllable and Guided Face Synthesis for Unconstrained Face Recognitioncited by 22
  14. 2022Cluster and Aggregate: Face Recognition with Large Probe Setcited by 22
  15. 2021Dual Spoof Disentanglement Generation for Face Anti-spoofing with Depth Uncertainty Learningcited by 20
  16. 2021Auto-Encoding Score Distribution Regression for Action Quality Assessmentcited by 18
  17. 2022Part-based Face Recognition with Vision Transformerscited by 18
  18. 2023Probabilistic Prompt Learning for Dense Predictioncited by 17
  19. 2023A Quality Aware Sample-to-Sample Comparison for Face Recognitioncited by 17
  20. 2024CRSOT: Cross-Resolution Object Tracking using Unaligned Frame and Event Camerascited by 17
  21. 2024Robust Multimodal Learning via Representation Decouplingcited by 17
  22. 2021Robust Depth Completion with Uncertainty-Driven Loss Functionscited by 16
  23. 2023Recognizability Embedding Enhancement for Very Low-Resolution Face Recognition and Quality Estimationcited by 16
  24. 2024Probabilistic Language-Image Pre-Trainingcited by 16
  25. 2022Out of Distribution Data Detection Using Dropout Bayesian Neural Networkscited by 15
  26. 2023Learning Sample Difficulty from Pre-trained Models for Reliable Predictioncited by 15
  27. 2021Quality-Aware Network for Human Parsingcited by 13
  28. 2022STUN: Self-Teaching Uncertainty Estimation for Place Recognitioncited by 13
  29. 2024TopoFR: A Closer Look at Topology Alignment on Face Recognitioncited by 13
  30. 2022Reliability-Aware Prediction via Uncertainty Learning for Person Image Retrievalcited by 12
  31. 2023Efficient Explainable Face Verification based on Similarity Score Argument Backpropagationcited by 12
  32. 2024SUMix: Mixup with Semantic and Uncertain Informationcited by 12
  33. 2024UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper Granularitycited by 12
  34. 2023Wrapped Cauchy Distributed Angular Softmax for Long-Tailed Visual Recognitioncited by 11
  35. 2025A Quality-Guided Mixture of Score-Fusion Experts Framework for Human Recognitioncited by 11
  36. 2021Deep Rival Penalized Competitive Learning for Low-resolution Face Recognitioncited by 10
  37. 2025Dynamic Uncertainty-aware Multimodal Fusion for Outdoor Health Monitoringcited by 10
  38. 2022Stating Comparison Score Uncertainty and Verification Decision Confidence Towards Transparent Face Recognitioncited by 9

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