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 face releated algorithm, datasets and papers

📝 Paper / Algorithm

Survey

  • Deep Face Recognition: A Survey paper
  • Face Recognition: From Traditional to Deep Learning Methods paper
  • Deep Facial Expression Recognition: A Survey paper
  • A Survey on Face Detection and Classification for Partially Occluded images paper
  • 3D face recognition: a survey paper
  • Face detection techniques: a review paper

2D- Face Recognition

2d_face_reg

[1] DeepID1 [paper]

Deep Learning Face Representation from Predicting 10,000 Classes

[2] DeepID2 [paper]

Deep Learning Face Representation by Joint Identification-Verification

[3] DeepID2+ [paper]

Deeply learned face representations are sparse, selective, and robust

[4] DeepIDv3 [paper]

DeepID3: Face Recognition with Very Deep Neural Networks

[5] Deep Face [paper]

Deep Face Recognition

[6] Center Loss [paper] [code]

A Discriminative Feature Learning Approach for Deep Face Recognition

[7]Marginal loss [paper]

Marginal loss for deep face recognition

[8] Range Loss[paper]

Range Loss for Deep Face Recognition with Long-tail

[9]Contrastive Loss [paper]

Deep learning face representation by joint identification-verification

[10] FaceNet [paper] [third-party implemention]

FaceNet: A Unified Embedding for Face Recognition and Clustering

[11] NormFace [paper] [code]

NormFace: L2 Hypersphere Embedding for Face Verification

[12] COCO Loss: [paper] [code]

Rethinking Feature Discrimination and Polymerization for Large-scale Recognition

[13] Large-Margin Softmax Loss [paper] [code]

Large-Margin Softmax Loss for Convolutional Neural Networks(L-Softmax loss)

[14]SphereFace: A-Softmax [paper] [code]

SphereFace: Deep Hypersphere Embedding for Face Recognition

[15]AM-Softmax/cosFace [paper AM-Softmax] [paper cosFace] [AM-softmax code]

AM : Additive Margin Softmax for Face Verification

CosFace: Large Margin Cosine Loss for Deep Face Recognition(Tencent AI Lab)

[16] ArcFace: [paper] [code]

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

[17] Adaptive Face paper

Adaptive Margin and Sampling for Face Recognition

[18] AdaCos Paper

Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations

[20] RegularFacepaper

Deep Face Recognition via Exclusive Regularization

[21] UniformFacepaper

Learning Deep Equidistributed Representation for Face Recognition

[22] P2SGradpaper

Refined Gradients for Optimizing Deep Face Models

cos_loss

Face Detection

[1] Cascade CNN [paper] [code]

A Convolutional Neural Network Cascade for Face Detection

[2] MTCNN [Paper] [code]

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

[3] ICC - CNN [paper]

Detecting Faces Using Inside Cascaded Contextual CNN

[4] Face R-CNN [Paper]

Face R-CNN

[5] Deep-IR[Paper]

Face Detection using Deep Learning: An Improved Faster RCNN Approach

[6] SSH [paper] [code]

SSH: Single Stage Headless Face Detector

[7] S3FD [paper]

Single Shot Scale-invariant Face Detector

[8] FaceBoxes [paper] [code]

Faceboxes: A CPU Real-time Face Detector with High Accuracy

[9] Scaleface [paper]

Face Detection through Scale-Friendly Deep Convolutional Networks

[10] HR [paper] [code]

Finding Tiny Faces

[11] FAN [paper]

Feature Agglomeration Networks for Single Stage Face Detection.

[12] PyramidBox [paper] [code]

PyramidBox: A Context-assisted Single Shot Face Detector

[13] SRN [paper]

Selective Refinement Network for High Performance Face Detection.

[14] DSFD [paper]

DSFD: Dual Shot Face Detector

[15] VIM FD [paper]

Robust and High Performance Face Detector

[16] ISRN [paper]

Improved Selective Refinement Network for Face Detection

[17] PyramidBox++ [Paper]

PyramidBox++: High Performance Detector for Finding Tiny Face

[18] RetinaFace [paper] [code]

RetinaFace: Single-stage Dense Face Localisation in the Wild

Face Alignment

[1] PRNet [paper] [code]

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

[2]LAB Paper [code]

Look at Boundary: A Boundary-Aware Face Alignment Algorithm

[3]PFLD Paper [demo code]

PFLD: A Practical Facial Landmark Detector

[4] 2D & 3D FAN [Paper] [code]

How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)

3D face reconstruction

[1] 3DMM

A Morphable Model For The Synthesis Of 3D Faces

[2] 3DDFA [paper] [github]

Face Alignment in Full Pose Range: A 3D Total Solution.

[3] VRN [index] [code]

Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression(3D Face Reconstruction from a Single Image)

[4] PRNet [paper] [github]

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

[5] 2DASL [paper] [github]

Joint 3D Face Reconstruction and Dense Face Alignment from A Single Image with 2D-Assisted Self-Supervised Learning

Face attack & Defends

[1] A Dataset and Benchmark for Large-Scale Multi-Modal Face Anti-Spoofing

[2] Deep Tree Learning for Zero-Shot Face Anti-Spoofing

[3] Decorrelated Adversarial Learning for Age-Invariant Face Recognition

[4] Multi-Adversarial Discriminative Deep Domain Generalization for Face Presentation Attack Detection

[5] Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition

⚙️ Open source lib

face recognition

face detection

📦 Datasets

2D Face Recognition

Datasets Description Links Publish Time
CASIA-WebFace 10,575 subjects and 494,414 images Download 2014
MegaFace🏅 1 million faces, 690K identities Download 2016
MS-Celeb-1M🏅 about 10M images for 100K celebrities Concrete measurement to evaluate the performance of recognizing one million celebrities Download 2016
LFW🏅 13,000 images of faces collected from the web. Each face has been labeled with the name of the person pictured. 1680 of the people pictured have two or more distinct photos in the data set. Download 2007
VGG Face2🏅 The dataset contains 3.31 million images of 9131 subjects (identities), with an average of 362.6 images for each subject. Download 2017
UMDFaces Dataset-image 367,888 face annotations for 8,277 subjects. Download 2016
Trillion Pairs🏅 Train: MS-Celeb-1M-v1c & Asian-Celeb Test: ELFW&DELFW Download 2018
FaceScrub It comprises a total of 106,863 face images of male and female 530 celebrities, with about 200 images per person. Download 2014
Mut1ny🏅 head/face segmentation dataset contains over 17.3k labeled images Download 2018
IMDB-Face The dataset contains about 1.7 million faces, 59k identities, which is manually cleaned from 2.0 million raw images. Download 2018
DiF 'Diversity in Faces' Dataset to Advance Study of Fairness in Facial Recognition Systems Download 2019
Megaface2 Level Playing Field for Million Scale Face Recognition(672K people in 4.7M images) Download 2019

Video face recognition

Datasets Description Links Publish Time
YouTube Face🏅 The data set contains 3,425 videos of 1,595 different people. Download 2011
UMDFaces Dataset-video🏅 Over 3.7 million annotated video frames from over 22,000 videos of 3100 subjects. Download 2017
PaSC The challenge includes 9,376 still images and 2,802 videos of 293 people. Download 2013
YTC The data consists of two parts: video clips (1910 sequences of 47 subjects) and initialization data(initial frame face bounding boxes, manually marked). Download 2008
iQIYI-VID🏅 The iQIYI-VID dataset contains 500,000 videos clips of 5,000 celebrities, adding up to 1000 hours. This dataset supplies multi-modal cues, including face, cloth, voice, gait, and subtitles, for character identification. Download 2018

3D face recognition

Datasets Description Links Publish Time
Bosphorus🏅 105 subjects and 4666 faces 2D & 3D face data Download 2008
BD-3DFE Analyzing Facial Expressions in 3D Space Download 2006
ND-2006 422 subjects and 9443 faces 3D Face Recognition Download 2006
FRGC V2.0 466 subjects and 4007 of 3D Face, Visible Face Images Download 2005
B3D(AC)^2 1000 high quality, dynamic 3D scans of faces, recorded while pronouncing a set of English sentences. Download 2010

Anti-spoofing

Datasets # of subj. / # of sess. Links Year Spoof attacks attacks Publish Time
NUAA 15/3 Download 2010 Print 2010
CASIA-MFSD 50/3 Download(link failed) 2012 Print, Replay 2012
Replay-Attack 50/1 Download 2012 Print, 2 Replay 2012
MSU-MFSD 35/1 Download 2015 Print, 2 Replay 2015
MSU-USSA 1140/1 Download 2016 2 Print, 6 Replay 2016
Oulu-NPU 55/3 Download 2017 2 Print, 6 Replay 2017
Siw 165/4 Download 2018 2 Print, 4 Replay 2018

Cross age and cross pose

Datasets Description Links Publish Time
CACD2000 The dataset contains more than 160,000 images of 2,000 celebrities with age ranging from 16 to 62. Download 2014
FGNet The dataset contains more than 1002 images of 82 people with age ranging from 0 to 69. Download 2000
MPRPH The MORPH database contains 55,000 images of more than 13,000 people within the age ranges of 16 to 77 Download 2016
CPLFW we construct a Cross-Pose LFW (CPLFW) which deliberately searches and selects 3,000 positive face pairs with pose difference to add pose variation to intra-class variance. Download 2017
CALFW Thereby we construct a Cross-Age LFW (CALFW) which deliberately searches and selects 3,000 positive face pairs with age gaps to add aging process intra-class variance. Download 2017

Face Detection

Datasets Description Links Publish Time
FDDB🏅 5171 faces in a set of 2845 images Download 2010
Wider-face 🏅 32,203 images and label 393,703 faces with a high degree of variability in scale, pose and occlusion, organized based on 61 event classes Download 2015
AFW AFW dataset is built using Flickr images. It has 205 images with 473 labeled faces. For each face, annotations include a rectangular bounding box6 landmarks and the pose angles. Download 2013
MALF MALF is the first face detection dataset that supports fine-gained evaluation. MALF consists of 5,250 images and 11,931 faces. Download 2015

Face Attributes

Datasets Description Links Key features Publish Time
CelebA 10,177 number of identities202,599 number of face images, and 5 landmark locations40 binary attributes annotations per image. Download attribute & landmark 2015
IMDB-WIKI 500k+ face images with age and gender labels Download age & gender 2015
Adience Unfiltered faces for gender and age classification Download age & gender 2014
WFLW🏅 WFLW contains 10000 faces (7500 for training and 2500 for testing) with 98 fully manual annotated landmarks. Download landmarks 2018
Caltech10k Web Faces The dataset has 10,524 human faces of various resolutions and in different settings Download landmarks 2005
EmotioNet The EmotioNet database includes950,000 images with annotated AUs. A subset of the images in the EmotioNet database correspond to basic and compound emotions. Download AU and Emotion 2017
RAF( Real-world Affective Faces) 29672 number of real-world images, including 7 classes of basic emotions and 12 classes of compound emotions, 5 accurate landmark locations37 automatic landmark locationsrace, age range and gender attributes annotations per image Download Emotions、landmark、race、age and gender 2017
FairFace FairFace: Face Attribute Dataset for Balanced RaceGender, and Age   balance race compoition 2019
LS3D-W A large-scale 3D face alignment dataset constructed by annotating the images from AFLW, 300VW, 300W and FDDB in a consistent manner with 68 points using the automatic method Download 3D landmark 2017

Others

Datasets Description Links Publish Time
IJB C/B/A🏅 IJB C/B/A is currently running three challenges related to face detection, verification, identification, and identity clustering. Download 2015
MOBIO bi-modal (audio and video) data taken from 152 people. Download 2012
BANCA The BANCA database was captured in four European languages in two modalities (face and voice). Download 2014
3D Mask Attack 76500 frames of 17 persons using Kinect RGBD with eye positions (Sebastien Marcel). Download 2013
WebCaricature 6042 caricatures and 5974 photographs from 252 persons collected from the web Download 2018

🏠 Research home(conf & workshop & trans)

Conference

ICCVIEEE International Conference on Computer Vision

CVPRIEEE Conference on Computer Vision and Pattern Recognition

ECCVEuropean Conference on Computer Vision

FGIEEE International Conference on Automatic Face and Gesture Recognition

BMVC: The British Machine Vision Conference

IJCB[ICB+BTAS]:International Joint Conference on Biometrics

AMFG: IEEE workshop on Analysis and Modeling of Faces and Gestures

Workshop on Biometrics

TPAMI: IEEE Transactions on Pattern Analysis and Machine Intelligence

IJCV: International Journal of Computer Vision

TIP: IEEE Transactions on Image Processing

TIFS: [IEEE Transactions on Information Forensics and Security](IEEE Transactions on Information Forensics and Security)

PR: Pattern Recognition

🏷 References

[1] https://github.com/RiweiChen/DeepFace/tree/master/FaceDataset

[2] https://www.zhihu.com/question/33505655?sort=created

[3] https://github.com/betars/Face-Resources

[4] https://zhuanlan.zhihu.com/p/33288325

[5] https://github.com/L706077/DNN-Face-Recognition-Papers

[6] https://www.zhihu.com/question/67919300

[7] https://jackietseng.github.io/conference_call_for_paper/2018-2019-conferences.html

[8]http://history.ccf.org.cn/sites/ccf/biaodan.jsp?contentId=2903940690839

[9]http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/WiderFace_Results.html

https://github.com/polarisZhao/awesome-face