mlsanityData to 14 Oct 2026

Face.evoLVe: A High-Performance Face Recognition Library

arXiv 2107.08621 ↗First posted 19 Jul 2021cs.CV cs.AI cs.MMcited by 26

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Abstract (arXiv)

In this paper, we develop face.evoLVe -- a comprehensive library that collects and implements a wide range of popular deep learning-based methods for face recognition. First of all, face.evoLVe is composed of key components that cover the full process of face analytics, including face alignment, data processing, various backbones, losses, and alternatives with bags of tricks for improving performance. Later, face.evoLVe supports multi-GPU training on top of different deep learning platforms, such as PyTorch and PaddlePaddle, which facilitates researchers to work on both large-scale datasets with millions of images and low-shot counterparts with limited well-annotated data. More importantly, along with face.evoLVe, images before & after alignment in the common benchmark datasets are released with source codes and trained models provided. All these efforts lower the technical burdens in reproducing the existing methods for comparison, while users of our library could focus on developing advanced approaches more efficiently. Last but not least, face.evoLVe is well designed and vibrantly evolving, so that new face recognition approaches can be easily plugged into our framework. Note that we have used face.evoLVe to participate in a number of face recognition competitions and secured the first place. The version that supports PyTorch is publicly available at https://github.com/ZhaoJ9014/face.evoLVe.PyTorch and the PaddlePaddle version is available at https://github.com/ZhaoJ9014/face.evoLVe.PyTorch/tree/master/paddle. Face.evoLVe has been widely used for face analytics, receiving 2.4K stars and 622 forks.

Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). Builds on 57 of its 101 references that are in the map. First posted on arXiv 19 Jul 2021.

Builds on

57 of 101 references.

References · 57

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  4. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  5. 2015Distilling the Knowledge in a Neural Networkcited by 10,324
  6. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  7. 2017Mask R-CNNcited by 7,277
  8. 2016Densely Connected Convolutional Networkscited by 6,720
  9. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
  10. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,475
  11. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 5,045
  12. 2017Squeeze-and-Excitation Networkscited by 4,789
38 more
  1. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
  2. 2014Going Deeper with Convolutionscited by 4,241
  3. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
  4. 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,849
  5. 2016Aggregated Residual Transformations for Deep Neural Networkscited by 2,546
  6. 2016Pyramid Scene Parsing Networkcited by 2,479
  7. 2017Rethinking Atrous Convolution for Semantic Image Segmentationcited by 2,161
  8. 2017Accurate, Large Minibatch SGD: Training ImageNet in 1 Hourcited by 1,492
  9. 2019Deep High-Resolution Representation Learning for Visual Recognitioncited by 1,420
  10. 2017ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devicescited by 1,200
  11. 2018ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Designcited by 1,136
  12. 2018CosFace: Large Margin Cosine Loss for Deep Face Recognitioncited by 971
  13. 2017VGGFace2: A dataset for recognising faces across pose and agecited by 914
  14. 2016Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networkscited by 903
  15. 2017SphereFace: Deep Hypersphere Embedding for Face Recognitioncited by 737
  16. 2016MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognitioncited by 624
  17. 2014Learning Face Representation from Scratchcited by 453
  18. 2017Age Progression/Regression by Conditional Adversarial Autoencodercited by 429
  19. 2019GhostNet: More Features from Cheap Operationscited by 410
  20. 2020Circle Loss: A Unified Perspective of Pair Similarity Optimizationcited by 403
  21. 2021MagFace: A Universal Representation for Face Recognition and Quality Assessmentcited by 334
  22. 2020CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognitioncited by 321
  23. 2018Additive Margin Softmax for Face Verificationcited by 278
  24. 2018Deep Face Recognition: A Surveycited by 276
  25. 2017Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environmentscited by 260
  26. 2021WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognitioncited by 223
  27. 2015The MegaFace Benchmark: 1 Million Faces for Recognition at Scalecited by 200
  28. 2015MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systemscited by 195
  29. 2015A Light CNN for Deep Face Representation with Noisy Labelscited by 126
  30. 2017Dual Path Networkscited by 119
  31. 2018A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillationcited by 110
  32. 2019AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representationscited by 83
  33. 2015DeepID3: Face Recognition with Very Deep Neural Networkscited by 62
  34. 2019CASIA-SURF: A Large-scale Multi-modal Benchmark for Face Anti-spoofingcited by 61
  35. 2019Mis-classified Vector Guided Softmax Loss for Face Recognitioncited by 60
  36. 2021FaceX-Zoo: A PyTorch Toolbox for Face Recognitioncited by 49
  37. 2017Level Playing Field for Million Scale Face Recognitioncited by 43
  38. 2016UMDFaces: An Annotated Face Dataset for Training Deep Networkscited by 42

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 7; 2023: 6; 2024: 5; 2025: 5; 2026: 1.

26 papers.

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  1. 2022POSTER: A Pyramid Cross-Fusion Transformer Network for Facial Expression Recognitioncited by 49
  2. 2022Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognitioncited by 26
  3. 2023Towards Real-World Blind Face Restoration with Generative Diffusion Priorcited by 22
  4. 2022Deep Convolutional Pooling Transformer for Deepfake Detectioncited by 19
  5. 2023What Should Be Balanced in a "Balanced" Face Recognition Dataset?cited by 13
  6. 2023Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attackscited by 13
  7. 2024Learning to Discover Forgery Cues for Face Forgery Detectioncited by 11
  8. 2021MLFW: A Database for Face Recognition on Masked Facescited by 10
  9. 2022How to Boost Face Recognition with StyleGAN?cited by 10
  10. 2021PP-HumanSeg: Connectivity-Aware Portrait Segmentation with a Large-Scale Teleconferencing Video Datasetcited by 9
  11. 2023ARBEx: Attentive Feature Extraction with Reliability Balancing for Robust Facial Expression Learningcited by 9
  12. 2022Face Recognition In Children: A Longitudinal Studycited by 7
14 more
  1. 2022AU-Aware Vision Transformers for Biased Facial Expression Recognitioncited by 4
  2. 2024Rank Matters: Understanding and Defending Model Inversion Attacks via Low-Rank Feature Filteringcited by 4
  3. 2024Clothes-Changing Person Re-Identification with Feasibility-Aware Intermediary Matchingcited by 2
  4. 2024Longitudinal Evaluation of Child Face Recognition and the Impact of Underlying Agecited by 2
  5. 2025Cross-Modal Distillation For Widely Differing Modalitiescited by 2
  6. 2023LPN: Language-guided Prototypical Network for few-shot classificationcited by 1
  7. 2025A Comparison of Human and Machine Learning Errors in Face Recognitioncited by 1
  8. 2025Generative Model Inversion Through the Lens of the Manifold Hypothesiscited by 1
  9. 2022AU-Supervised Convolutional Vision Transformers for Synthetic Facial Expression Recognitioncited by 0
  10. 20231DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Trackingcited by 0
  11. 2024GReFEL: Geometry-Aware Reliable Facial Expression Learning under Bias and Imbalanced Data Distributioncited by 0
  12. 2025PEEL the Layers and Find Yourself: Revisiting Inference-time Data Leakage for Residual Neural Networkscited by 0
  13. 2025SoK: On the Survivability of Backdoor Attacks on Unconstrained Face Recognition Systemscited by 0
  14. 2026Low-rank Orthogonal Subspace Intervention for Generalizable Face Forgery Detectioncited by 0