Face Recognition

Papers

Deep Learning Face Representation from Predicting 10,000 Classes

• intro: CVPR 2014. DeepID
• paper: http://mmlab.ie.cuhk.edu.hk/pdf/YiSun_CVPR14.pdf
• github: https://github.com/stdcoutzyx/DeepID_FaceClassify

基于Caffe的DeepID2实现

• 1. http://www.miaoerduo.com/deep-learning/%E5%9F%BA%E4%BA%8Ecaffe%E7%9A%84deepid2%E5%AE%9E%E7%8E%B0%EF%BC%88%E4%B8%8A%EF%BC%89.html
• 1. http://www.miaoerduo.com/deep-learning/%E5%9F%BA%E4%BA%8Ecaffe%E7%9A%84deepid2%E5%AE%9E%E7%8E%B0%EF%BC%88%E4%B8%AD%EF%BC%89.html
• 1. http://www.miaoerduo.com/deep-learning/%E5%9F%BA%E4%BA%8Ecaffe%E7%9A%84deepid2%E5%AE%9E%E7%8E%B0%EF%BC%88%E4%B8%8B%EF%BC%89.html

Deeply learned face representations are sparse, selective, and robust

• intro: DeepID2+
• arxiv: http://arxiv.org/abs/1412.1265
• video: http://research.microsoft.com/apps/video/?id=260023
• mirror: http://pan.baidu.com/s/1boufl3x

MobileID: Face Model Compression by Distilling Knowledge from Neurons

• intro: AAAI 2016 Oral. CUHK
• intro: MobileID is an extremely fast face recognition system by distilling knowledge from DeepID2
• project page: http://personal.ie.cuhk.edu.hk/~lz013/projects/MobileID.html
• paper: http://personal.ie.cuhk.edu.hk/~pluo/pdf/aaai16-face-model-compression.pdf
• github: https://github.com/liuziwei7/mobile-id

Deep Face Recognition

• intro: BMVC 2015
• paper: http://www.robots.ox.ac.uk/~vgg/publications/2015/Parkhi15/parkhi15.pdf
• homepage: http://www.robots.ox.ac.uk/~vgg/software/vgg_face/
• github(Keras): https://github.com/rcmalli/keras-vggface

FaceNet

FaceNet: A Unified Embedding for Face Recognition and Clustering

• intro: Google Inc. CVPR 2015
• arxiv: http://arxiv.org/abs/1503.03832
• github(Tensorflow): https://github.com/davidsandberg/facenet
• github(Caffe): https://github.com/hizhangp/triplet

Real time face detection and recognition

• intro: Real time face detection and recognition base on opencv/tensorflow/mtcnn/facenet
• github: https://github.com/shanren7/real_time_face_recognition

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Targeting Ultimate Accuracy: Face Recognition via Deep Embedding

• intro: CVPR 2015
• arxiv: http://arxiv.org/abs/1506.07310

Learning Robust Deep Face Representation

• arxiv: https://arxiv.org/abs/1507.04844

A Light CNN for Deep Face Representation with Noisy Labels

• arxiv: https://arxiv.org/abs/1511.02683
• github: https://github.com/AlfredXiangWu/face_verification_experiment

Pose-Aware Face Recognition in the Wild

• paper: www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Masi_Pose-Aware_Face_Recognition_CVPR_2016_paper.pdf

Recurrent Regression for Face Recognition

• arxiv: http://arxiv.org/abs/1607.06999

A Discriminative Feature Learning Approach for Deep Face Recognition

• intro: ECCV 2016
• intro: center loss
• paper: http://ydwen.github.io/papers/WenECCV16.pdf
• github: https://github.com/ydwen/caffe-face
• github: https://github.com/pangyupo/mxnet_center_loss

Deep Face Recognition with Center Invariant Loss

• intro: ACM MM Workshop
• paper: http://www1.ece.neu.edu/~yuewu/files/2017/twu024.pdf

How Image Degradations Affect Deep CNN-based Face Recognition?

• arxiv: http://arxiv.org/abs/1608.05246

VIPLFaceNet: An Open Source Deep Face Recognition SDK

• keywords: VIPLFaceNet / SeetaFace Engine
• arxiv: http://arxiv.org/abs/1609.03892

SeetaFace Engine

• intro: SeetaFace Engine is an open source C++ face recognition engine, which can run on CPU with no third-party dependence.
• github: https://github.com/seetaface/SeetaFaceEngine

A Discriminative Feature Learning Approach for Deep Face Recognition

• intro: ECCV 2016
• paper: http://ydwen.github.io/papers/WenECCV16.pdf

Sparsifying Neural Network Connections for Face Recognition

• paper: http://www.ee.cuhk.edu.hk/~xgwang/papers/sunWTcvpr16.pdf

Range Loss for Deep Face Recognition with Long-tail

• arxiv: https://arxiv.org/abs/1611.08976

Towards End-to-End Face Recognition through Alignment Learning

• intro: Tsinghua University
• arxiv: https://arxiv.org/abs/1701.07174

Multi-Task Convolutional Neural Network for Face Recognition

• arxiv: https://arxiv.org/abs/1702.04710

SphereFace: Deep Hypersphere Embedding for Face Recognition

• intro: CVPR 2017
• arxiv: http://wyliu.com/papers/LiuCVPR17.pdf
• github: https://github.com/wy1iu/sphereface
• demo: http://v-wb.youku.com/v_show/id_XMjk3NTc1NjMxMg==.html

Learning towards Minimum Hyperspherical Energy

• intro: NeurIPS 2018
• keywords: SphereFace+
• arxiv: https://arxiv.org/abs/1805.09298
• github: https://github.com/wy1iu/sphereface-plus

Low Resolution Face Recognition Using a Two-Branch Deep Convolutional Neural Network Architecture

• intro: Amirkabir University of Technology & MIT
• arxiv: https://arxiv.org/abs/1706.06247

Enhancing Convolutional Neural Networks for Face Recognition with Occlusion Maps and Batch Triplet Loss

https://arxiv.org/abs/1707.07923

Improving Heterogeneous Face Recognition with Conditional Adversarial Networks

https://arxiv.org/abs/1709.02848

Face Sketch Matching via Coupled Deep Transform Learning

• intro: ICCV 2017
• arxiv: https://arxiv.org/abs/1710.02914

Face Recognition via Centralized Coordinate Learning

• intro: centralized coordinate learning (CCL)
• arxiv: https://arxiv.org/abs/1801.05678

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

• arxiv: https://arxiv.org/abs/1801.07698
• github: https://github.com/deepinsight/insightface

CosFace: Large Margin Cosine Loss for Deep Face Recognition

https://arxiv.org/abs/1801.09414

Ring loss: Convex Feature Normalization for Face Recognition

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1803.00130

Pose-Robust Face Recognition via Deep Residual Equivariant Mapping

• intro: CVPR 2018. CUHK & SenseTime Research
• arxiv: https://arxiv.org/abs/1803.00839
• github: https://github.com/penincillin/DREAM

Deep Face Recognition: A Survey

• intro: BUPT
• arxiv: https://arxiv.org/abs/1804.06655

Surveillance Face Recognition Challenge

https://arxiv.org/abs/1804.09691

Towards Interpretable Face Recognition

https://arxiv.org/abs/1805.00611

Scalable Angular Discriminative Deep Metric Learning for Face Recognition

https://arxiv.org/abs/1804.10899

Minimum Margin Loss for Deep Face Recognition

https://arxiv.org/abs/1805.06741

Wildest Faces: Face Detection and Recognition in Violent Settings

https://arxiv.org/abs/1805.07566

Deep Imbalanced Learning for Face Recognition and Attribute Prediction

https://arxiv.org/abs/1806.00194

Accurate and Efficient Similarity Search for Large Scale Face Recognition

• intro: BUPT
• arxiv: https://arxiv.org/abs/1806.00365

Face Recognition in Low Quality Images: A Survey

https://arxiv.org/abs/1805.11519

Low Resolution Face Recognition in the Wild

https://arxiv.org/abs/1805.11529

From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data

• intro: ECCV 2018
• arxiv: https://arxiv.org/abs/1807.07872

Git Loss for Deep Face Recognition

• intro: BMVC 2018
• arxiv: https://arxiv.org/abs/1807.08512

Multicolumn Networks for Face Recognition

• intro: BMVC 2018
• arxiv: https://arxiv.org/abs/1807.09192

The Devil of Face Recognition is in the Noise

• intro: ECCV 2018
• arxiv: https://arxiv.org/abs/1807.11649
• paper: http://openaccess.thecvf.com/content_ECCV_2018/papers/Liren_Chen_The_Devil_of_ECCV_2018_paper.pdf
• dataset: https://github.com/fwang91/IMDb-Face

Deep Sketch-Photo Face Recognition Assisted by Facial Attributes

https://arxiv.org/abs/1808.00059

Global Norm-Aware Pooling for Pose-Robust Face Recognition at Low False Positive Rate

https://arxiv.org/abs/1808.00435

Pairwise Relational Networks for Face Recognition

• intro: ECCV 2018
• arxiv: https://arxiv.org/abs/1808.04976

Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition

https://arxiv.org/abs/1810.07599

Pairwise Relational Networks using Local Appearance Features for Face Recognition

• intro: NIPS 2018 R2L workshop
• arxiv: https://arxiv.org/abs/1811.06405

Low-resolution Face Recognition in the Wild via Selective Knowledge Distillation

https://arxiv.org/abs/1811.09998

Low-Resolution Face Recognition

• arxiv: https://arxiv.org/abs/1811.08965
• dataset: https://qmul-tinyface.github.io/

MobiFace: A Lightweight Deep Learning Face Recognition on Mobile Devices

https://arxiv.org/abs/1811.11080

Attacks on State-of-the-Art Face Recognition using Attentional Adversarial Attack Generative Network

https://arxiv.org/abs/1811.12026

Support Vector Guided Softmax Loss for Face Recognition

• intro: JD AI research & Chinese Academy of Science
• arxiv: https://arxiv.org/abs/1812.11317

Linkage Based Face Clustering via Graph Convolution Network

• intro: CVPR 2019
• arxiv: https://arxiv.org/abs/1903.11306

Deep Learning for Face Recognition: Pride or Prejudiced?

https://arxiv.org/abs/1904.01219

Efficient Decision-based Black-box Adversarial Attacks on Face Recognition

• intro: CVPR 2019
• arxiv: https://arxiv.org/abs/1904.04433

Decorrelated Adversarial Learning for Age-Invariant Face Recognition

• intro: Tencent AI Lab
• arxiv: https://arxiv.org/abs/1904.04972

ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student Networks

https://arxiv.org/abs/1905.10620

Attentional Feature-Pair Relation Networks for Accurate Face Recognition

https://arxiv.org/abs/1908.06255

Occlusion Robust Face Recognition Based on Mask Learning with PairwiseDifferential Siamese Network

https://arxiv.org/abs/1908.06290

Towards Flops-constrained Face Recognition

• intro: ICCV 2019 LFR workshop
• arxiv: https://arxiv.org/abs/1909.00632

VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight Face Recognition

• intro: ICCV workshop 2019, champion of deepglintlight track of LFR (2019) challenge
• intro: Horizon Robotics
• arxiv: https://arxiv.org/abs/1910.04985
• paper: http://openaccess.thecvf.com/content_ICCVW_2019/papers/LSR/Yan_VarGFaceNet_An_Efficient_Variable_Group_Convolutional_Neural_Network_for_Lightweight_ICCVW_2019_paper.pdf
• github: https://github.com/zma-c-137/VarGFaceNet

Towards Flops-constrained Face Recognition

• intro: ICCV 2019 LFR workshop
• intro: 1st place in the ICCV19 Lightweight Face Recognition Challenge, large video track
• keywords: Trojans
• arxiv: https://arxiv.org/abs/1909.00632
• paper: https://github.com/sciencefans/trojans-face-recognizer

Unknown Identity Rejection Loss: Utilizing Unlabeled Data for Face Recognition

• intro: ICCV 2019 Lightweight Face Recognition Challenge & Workshop
• arxiv: https://arxiv.org/abs/1910.10896

FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization

• intro: Michigan State University & Youtu Lab, Tencent & Microsoft Cloud and AI & Zhejiang University
• arxiv: https://arxiv.org/abs/1911.11680

Mis-classified Vector Guided Softmax Loss for Face Recognition

• intro: AAAI 2019 oral
• arxiv: https://arxiv.org/abs/1912.00833

Domain Balancing: Face Recognition on Long-Tailed Domains

• intro: CVPR 2020
• intro: Chinese Academy of Sciences & Tianjin University
• arxiv: https://arxiv.org/abs/2003.13791

CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition

• intro: CVPR 2020
• intro: Youtu Lab, Tencent & Zhejiang University & Michigan State University
• arixv: https://arxiv.org/abs/2004.00288
• github: https://github.com/HuangYG123/CurricularFace

Loss Function Search for Face Recognition

• intro: ICML 2020
• arxiv: https://arxiv.org/abs/2007.06542

Explainable Face Recognition

• intro: ECCV 2020
• project page: https://stresearch.github.io/xfr/
• arxiv: https://arxiv.org/abs/2008.00916
• github: https://github.com/stresearch/xfr

BroadFace: Looking at Tens of Thousands of People at Once for Face Recognition

• intro: ECCV 2020
• arxiv: https://arxiv.org/abs/2008.06674

Searching for Alignment in Face Recognition

• intro: AAAI 2021
• arxiv: https://arxiv.org/abs/2102.05447

When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework

• intro: CVPR 2021
• intro: Fudan University
• arxiv: https://arxiv.org/abs/2103.01520
• github: https://github.com/Hzzone/MTLFace

Unmasking Face Embeddings by Self-restrained Triplet Loss for Accurate Masked Face Recognition

https://arxiv.org/abs/2103.01716

WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition

• intro: CVPR 2021
• intro: Tsinghua University & XForwardAI & Imperial College London
• project page: https://www.face-benchmark.org/
• arxiv: https://arxiv.org/abs/2103.04098

Face Transformer for Recognition

• intro: Beijing University of Posts and Telecommunications
• arxiv: https://arxiv.org/abs/2103.14803

MagFace: A Universal Representation for Face Recognition and Quality Assessment

• intro: CVPR 2021 oral
• intro: Algorithm Research, Aibee Inc.
• arxiv: https://arxiv.org/abs/2103.06627
• github: https://github.com/IrvingMeng/MagFace

Dynamic Class Queue for Large Scale Face Recognition In the Wild

• intro: CVPR 2021
• arxiv: https://arxiv.org/abs/2105.11113
• github: https://github.com/bilylee/DCQ

End2End Occluded Face Recognition by Masking Corrupted Features

• intro: TPAMI 2021
• arxiv: https://arxiv.org/abs/2108.09468

AdaFace: Quality Adaptive Margin for Face Recognition

• intro: CVPR 2022 oral
• arxiv: https://arxiv.org/abs/2204.00964
• github: https://github.com/mk-minchul/AdaFace

CoupleFace: Relation Matters for Face Recognition Distillation

• intro: Beihang University & SenseTime Group Limited & The University of Sydney
• arxiv: https://arxiv.org/abs/2204.05502

Face Verification

Deep Learning Face Representation by Joint Identification-Verification

• intro: DeepID2
• paper: http://papers.nips.cc/paper/5416-analog-memories-in-a-balanced-rate-based-network-of-e-i-neurons

DeepFace: Closing the Gap to Human-Level Performance in Face Verification

• intro: CVPR 2014. Facebook AI Research
• paper: https://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf
• slides: http://valse.mmcheng.net/ftp/20141126/MingYang.pdf
• github: https://github.com/RiweiChen/DeepFace

Triplet Probabilistic Embedding for Face Verification and Clustering

• intro: Oral Paper in BTAS 2016; NVIDIA Best paper Award
• arxiv: https://arxiv.org/abs/1604.05417
• github(Keras): https://github.com/meownoid/face-identification-tpe

DeMeshNet: Blind Face Inpainting for Deep MeshFace Verification

https://arxiv.org/abs/1611.05271

Hybrid Deep Learning for Face Verification

• intro: TPAMI 2016. CNN+RBM
• paper: http://www.ee.cuhk.edu.hk/~xgwang/papers/sunWTpami16.pdf

NormFace: L2 Hypersphere Embedding for Face Verification

• arxiv: https://arxiv.org/abs/1704.06369
• github: https://github.com/happynear/NormFace

L2-constrained Softmax Loss for Discriminative Face Verification

https://arxiv.org/abs/1703.09507

von Mises-Fisher Mixture Model-based Deep learning: Application to Face Verification

https://arxiv.org/abs/1706.04264

Model Distillation with Knowledge Transfer in Face Classification, Alignment and Verification

https://arxiv.org/abs/1709.02929

Additive Margin Softmax for Face Verification

• keywords: additive margin Softmax (AM-Softmax),
• arxiv: https://arxiv.org/abs/1801.05599
• github: https://github.com/happynear/AMSoftmax

MobileFaceNets: Efficient CNNs for Accurate Real-time Face Verification on Mobile Devices

• intro: Beijing Jiaotong University & Watchdata Inc
• arxiv: https://arxiv.org/abs/1804.07573

DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild

https://arxiv.org/abs/1804.09669

An Experimental Evaluation of Covariates Effects on Unconstrained Face Verification

https://arxiv.org/abs/1808.05508

Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-Resolution Network

https://arxiv.org/abs/1903.10974

xCos: An Explainable Cosine Metric for Face Verification Task

https://arxiv.org/abs/2003.05383

Facial Attributes Classification

A Jointly Learned Deep Architecture for Facial Attribute Analysis and Face Detection in the Wild

https://arxiv.org/abs/1707.08705

A Deep Cascade Network for Unaligned Face Attribute Classification

https://arxiv.org/abs/1709.03851

A Deep Face Identification Network Enhanced by Facial Attributes Prediction

https://arxiv.org/abs/1805.00324

Multi-task Learning of Cascaded CNN for Facial Attribute Classification

• intro: Xiamen University & Xiamen University of Technology
• arxiv: https://arxiv.org/abs/1805.01290

Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification

• intro: Xiamen University & Xiamen University of Technology
• arxiv: https://arxiv.org/abs/1805.01282

A Survey to Deep Facial Attribute Analysis

https://arxiv.org/abs/1812.10265

Registration-free Face-SSD: Single shot analysis of smiles, facial attributes, and affect in the wild

• intro: Elsevier CVIU 2019
• arxiv: https://arxiv.org/abs/1902.04042

Video Face Recognition

Neural Aggregation Network for Video Face Recognition

• intro: CVPR 2017
• keywords: Neural Aggregation Network (NAN)
• arxiv: https://arxiv.org/abs/1603.05474

Attention-Set based Metric Learning for Video Face Recognition

https://arxiv.org/abs/1704.03805

SeqFace: Make full use of sequence information for face recognitio

• arxiv: https://arxiv.org/abs/1803.06524
• github: https://github.com/huangyangyu/SeqFace

Video Face Recognition: Component-wise Feature Aggregation Network (C-FAN)

• intro: Michigan State University
• arxiv: https://arxiv.org/abs/1902.07327

Facial Point / Landmark Detection

Deep Convolutional Network Cascade for Facial Point Detection

• homepage: http://mmlab.ie.cuhk.edu.hk/archive/CNN_FacePoint.htm
• paper: http://www.ee.cuhk.edu.hk/~xgwang/papers/sunWTcvpr13.pdf
• github: https://github.com/luoyetx/deep-landmark

Facial Landmark Detection by Deep Multi-task Learning

• intro: ECCV 2014
• project page: http://mmlab.ie.cuhk.edu.hk/projects/TCDCN.html
• paper: http://personal.ie.cuhk.edu.hk/~ccloy/files/eccv_2014_deepfacealign.pdf
• github(Matlab): https://github.com/zhzhanp/TCDCN-face-alignment

A Recurrent Encoder-Decoder Network for Sequential Face Alignment

• intro: ECCV 2016 oral
• project page: https://sites.google.com/site/xipengcshomepage/eccv2016
• arxiv: https://arxiv.org/abs/1608.05477
• slides: https://drive.google.com/file/d/0B-FLp_bljv_1OTVrMF9OM21IbW8/view
• github: https://github.com/xipeng13/recurrent-face-alignment

RED-Net: A Recurrent Encoder-Decoder Network for Video-based Face Alignment

• intro: IJCV
• arxiv: https://arxiv.org/abs/1801.06066

Detecting facial landmarks in the video based on a hybrid framework

• arxiv: http://arxiv.org/abs/1609.06441

Deep Constrained Local Models for Facial Landmark Detection

• arxiv: https://arxiv.org/abs/1611.08657

Effective face landmark localization via single deep network

• arxiv: https://arxiv.org/abs/1702.02719

A Convolution Tree with Deconvolution Branches: Exploiting Geometric Relationships for Single Shot Keypoint Detection

https://arxiv.org/abs/1704.01880

Deep Alignment Network: A convolutional neural network for robust face alignment

• intro: CVPRW 2017
• arxiv: https://arxiv.org/abs/1706.01789
• gihtub: https://github.com/MarekKowalski/DeepAlignmentNetwork

Joint Multi-view Face Alignment in the Wild

https://arxiv.org/abs/1708.06023

FacePoseNet: Making a Case for Landmark-Free Face Alignment

https://arxiv.org/abs/1708.07517

Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks

https://arxiv.org/abs/1711.06753

Brute-Force Facial Landmark Analysis With A 140,000-Way Classifier

• intro: AAAI 2018
• arxiv: https://arxiv.org/abs/1802.01777
• github: https://github.com/mtli/BFFL

Style Aggregated Network for Facial Landmark Detection

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1803.04108
• github: https://github.com/D-X-Y/SAN

Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment

https://arxiv.org/abs/1803.05588

Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors

• intro: Minor modifications to the CVPR 2018 version (add missing references)
• arxiv: https://arxiv.org/abs/1807.00966

Deep Multi-Center Learning for Face Alignment

• arxiv: https://arxiv.org/abs/1808.01558
• github: https://github.com/ZhiwenShao/MCNet-Extension

Hierarchical binary CNNs for landmark localization with limited resources

• intro: TPAMI 2018
• arxiv: https://arxiv.org/abs/1808.04803

Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos

• intro: AAAI 2019
• arxiv: https://arxiv.org/abs/1811.00342
• github: https://github.com/tyshiwo/FHR_alignment

Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment

https://arxiv.org/abs/1812.01936

PFLD: A Practical Facial Landmark Detector

• arxiv: https://arxiv.org/abs/1902.10859
• github: https://github.com/guoqiangqi/PFLD

Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection

• intro: CVPR 2019
• arxiv: https://arxiv.org/abs/1903.10661

An Efficient Multitask Neural Network for Face Alignment, Head Pose Estimation and Face Tracking

• intro: University of Technology Sydney
• arxiv: https://arxiv.org/abs/2103.07615

HIH: Towards More Accurate Face Alignment via Heatmap in Heatmap

https://arxiv.org/abs/2104.03100

Subpixel Heatmap Regression for Facial Landmark Localization

• intro: BMVC 2021
• intro: Samsung AI Center, Cambridge, UK & Queen Mary University London
• project page: https://www.adrianbulat.com/face-alignment
• arxiv: https://arxiv.org/abs/2111.02360
• github: https://github.com/1adrianb/face-alignment

RePFormer: Refinement Pyramid Transformer for Robust Facial Landmark Detection

• intro: The Chinese University of Hong Kong & The Hong Kong University of Science and Technology & IIAI & Terminus Group & Chinese Academy of Sciences
• arxiv: https://arxiv.org/abs/2207.03917

Face Synthesis

Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis

• intro: ICCV 2017
• keywords: TP-GAN
• arxiv: https://arxiv.org/abs/1704.04086
• paper: http://openaccess.thecvf.com/content_ICCV_2017/papers/Huang_Beyond_Face_Rotation_ICCV_2017_paper.pdf
• github(official, Tensorflow): https://github.com/HRLTY/TP-GAN

Projects

Using MXNet for Face-related Algorithm

• github: https://github.com/tornadomeet/mxnet-face

clmtrackr: Javascript library for precise tracking of facial features via Constrained Local Models

• github: https://github.com/auduno/clmtrackr
• blog: http://auduno.com/post/61888277175/fitting-faces
• demo: http://auduno.github.io/clmtrackr/examples/facesubstitution.html
• demo: http://auduno.github.io/clmtrackr/face_deformation_video.html
• demo: http://auduno.github.io/clmtrackr/examples/clm_emotiondetection.html
• demo: http://auduno.com/post/84214587523/twisting-faces

DeepLogo

• intro: A brand logo recognition system using deep convolutional neural networks.
• github: https://github.com/satojkovic/DeepLogo

Deep-Leafsnap

• intro: LeafSnap replicated using deep neural networks to test accuracy compared to traditional computer vision methods.
• github: https://github.com/sujithv28/Deep-Leafsnap

FaceVerification: An Experimental Implementation of Face Verification, 96.8% on LFW

• github: https://github.com/happynear/FaceVerification

InsightFace

• intro: Face Recognition Project on MXnet
• arxiv: https://github.com//deepinsight/insightface

OpenFace

OpenFace: Face Recognition with Deep Neural Networks

• homepage: http://cmusatyalab.github.io/openface/
• github: https://github.com/cmusatyalab/openface
• github: https://github.com/aybassiouny/OpenFaceCpp

OpenFace 0.2.0: Higher accuracy and halved execution time

• homepage: http://bamos.github.io/2016/01/19/openface-0.2.0/

OpenFace: A general-purpose face recognition library with mobile applications

• paper: http://reports-archive.adm.cs.cmu.edu/anon/anon/usr0/ftp/2016/CMU-CS-16-118.pdf

OpenFace: an open source facial behavior analysis toolkit

• intro: a state-of-the art open source tool intended for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation.
• github: https://github.com/TadasBaltrusaitis/OpenFace

Resources

Face-Resources

• github: https://github.com/betars/Face-Resources