mlsanityData to 7 Oct 2026

Deep Learning Face Representation by Joint Identification-Verification

arXiv 1406.4773 ↗First posted 18 Jun 2014cs.CVcited by 162

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Abstract (arXiv)

The key challenge of face recognition is to develop effective feature representations for reducing intra-personal variations while enlarging inter-personal differences. In this paper, we show that it can be well solved with deep learning and using both face identification and verification signals as supervision. The Deep IDentification-verification features (DeepID2) are learned with carefully designed deep convolutional networks. The face identification task increases the inter-personal variations by drawing DeepID2 extracted from different identities apart, while the face verification task reduces the intra-personal variations by pulling DeepID2 extracted from the same identity together, both of which are essential to face recognition. The learned DeepID2 features can be well generalized to new identities unseen in the training data. On the challenging LFW dataset, 99.15% face verification accuracy is achieved. Compared with the best deep learning result on LFW, the error rate has been significantly reduced by 67%.

Key facts. Cited by 162 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jun 2014.

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Citing papers per year: 2021: 51; 2022: 41; 2023: 32; 2024: 18; 2025: 14; 2026: 6.

162 papers.

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  1. 2023Improving and generalizing flow-based generative models with minibatch optimal transportcited by 835
  2. 2023TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinementcited by 281
  3. 2022TAP-Vid: A Benchmark for Tracking Any Point in a Videocited by 258
  4. 2022CelebV-HQ: A Large-Scale Video Facial Attributes Datasetcited by 246
  5. 2021WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognitioncited by 221
  6. 2021FSCE: Few-Shot Object Detection via Contrastive Proposal Encodingcited by 168
  7. 2022Meta Balanced Network for Fair Face Recognitioncited by 53
  8. 2023GeneCIS: A Benchmark for General Conditional Image Similaritycited by 46
  9. 2021SphereFace2: Binary Classification is All You Need for Deep Face Recognitioncited by 42
  10. 2021Masked Face Recognition Challenge: The InsightFace Track Reportcited by 41
  11. 2022WebFace260M: A Benchmark for Million-Scale Deep Face Recognitioncited by 41
  12. 2021DISSECT: Disentangled Simultaneous Explanations via Concept Traversalscited by 37
38 more
  1. 2024FaceXFormer: A Unified Transformer for Facial Analysiscited by 34
  2. 2021Learning Rich Features for Gait Recognition by Integrating Skeletons and Silhouettescited by 29
  3. 2021SphereFace Revived: Unifying Hyperspherical Face Recognitioncited by 23
  4. 2022OPOM: Customized Invisible Cloak towards Face Privacy Protectioncited by 22
  5. 2023Controllable Inversion of Black-Box Face Recognition Models via Diffusioncited by 22
  6. 2021Structure-Aware Face Clustering on a Large-Scale Graph with bf107 Nodescited by 21
  7. 2022SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognitioncited by 21
  8. 2022Evaluation-oriented Knowledge Distillation for Deep Face Recognitioncited by 19
  9. 2021Dodging Attack Using Carefully Crafted Natural Makeupcited by 17
  10. 2023A Quality Aware Sample-to-Sample Comparison for Face Recognitioncited by 17
  11. 20211xN Pattern for Pruning Convolutional Neural Networkscited by 16
  12. 2022GAN-based Facial Attribute Manipulationcited by 16
  13. 2023Recognizability Embedding Enhancement for Very Low-Resolution Face Recognition and Quality Estimationcited by 16
  14. 2021LARNet: Lie Algebra Residual Network for Face Recognitioncited by 14
  15. 2021FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systemscited by 14
  16. 2021CoReS: Compatible Representations via Stationaritycited by 14
  17. 2021Searching for Alignment in Face Recognitioncited by 12
  18. 2022A Deep Dive into Dataset Imbalance and Bias in Face Identificationcited by 11
  19. 2025Prototype-Driven Structure Synergy Network for Remote Sensing Images Segmentationcited by 11
  20. 2021Large-Scale Training System for 100-Million Classification at Alibabacited by 10
  21. 2021Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learningcited by 10
  22. 2021Deep Rival Penalized Competitive Learning for Low-resolution Face Recognitioncited by 10
  23. 2022ELM: Embedding and Logit Margins for Long-Tail Learningcited by 10
  24. 2022Blind Face Restoration: Benchmark Datasets and a Baseline Modelcited by 10
  25. 2023UniTSFace: Unified Threshold Integrated Sample-to-Sample Loss for Face Recognitioncited by 10
  26. 2023Cross Architecture Distillation for Face Recognitioncited by 9
  27. 2024Face De-identification: State-of-the-art Methods and Comparative Studiescited by 9
  28. 2021Discovering conservation laws from trajectories via machine learningcited by 8
  29. 2021GAM: Explainable Visual Similarity and Classification via Gradient Activation Mapscited by 8
  30. 2021Dynamic Modeling of Hand-Object Interactions via Tactile Sensingcited by 8
  31. 2022CoupleFace: Relation Matters for Face Recognition Distillationcited by 8
  32. 2022Task Agnostic and Post-hoc Unseen Distribution Detectioncited by 8
  33. 2024VariFace: Fair and Diverse Synthetic Dataset Generation for Face Recognitioncited by 8
  34. 2021A Novel Automatic Modulation Classification Scheme Based on Multi-Scale Networkscited by 7
  35. 2022MorDeephy: Face Morphing Detection Via Fused Classificationcited by 7
  36. 2022Towards Explaining Demographic Bias through the Eyes of Face Recognition Modelscited by 7
  37. 2022The Impact of Racial Distribution in Training Data on Face Recognition Bias: A Closer Lookcited by 7
  38. 2023Gradient Attention Balance Network: Mitigating Face Recognition Racial Bias via Gradient Attentioncited by 7

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