人臉識別[一] 演算法和資料庫總結
Face-Resources
Following is a growing list of some of the materials I found on the web for research on face recognition algorithm。
Papers
1。 [DeepFace](
https://www。
cs。toronto。edu/~ranzato
/publications/taigman_cvpr14。pdf
)。A work from Facebook。
2。 [FaceNet](
http://www。
cv-foundation。org/opena
ccess/content_cvpr_2015/app/1A_089。pdf
)。A work from Google。
3。 [ One Millisecond Face Alignment with an Ensemble of Regression Trees](
http://www。
csc。kth。se/~vahidk/pape
rs/KazemiCVPR14。pdf
)。 Dlib implements the algorithm。
4。 [DeepID](
http://
mmlab。ie。cuhk。edu。hk/pd
f/YiSun_CVPR14。pdf
)
5。 [DeepID2]([1406。4773] Deep Learning Face Representation by Joint Identification-Verification)
6。 [DeepID3](Face Recognition with Very Deep Neural Networks)
7。 [Learning Face Representation from Scratch]([1411。7923] Learning Face Representation from Scratch)
8。 [Face Search at Scale: 80 Million Gallery](80 Million Gallery)
9。 [A Discriminative Feature Learning Approach for Deep Face Recognition](
http://
ydwen。github。io/papers/
WenECCV16。pdf
)
10。 [NormFace: L2 Hypersphere Embedding for Face Verification](
https://
arxiv。org/abs/1704。0636
9
)。* attention: model released !*
11。 [SphereFace: Deep Hypersphere Embedding for Face Recognition](Deep Hypersphere Embedding for Face Recognition)
12。[VGGFace2: A dataset for recognising faces across pose and age ]A dataset for recognising faces across pose and age
Datasets
1。 [CASIA WebFace Database](Center for Biometrics and Security Research)。 10,575 subjects and 494,414 images
2。 [Labeled Faces in the Wild](
http://
vis-www。cs。umass。edu/lf
w/
)。13,000 images and 5749 subjects
3。 [Large-scale CelebFaces Attributes (CelebA) Dataset](403 Forbidden) 202,599 images and 10,177 subjects。 5 landmark locations, 40 binary attributes。
4。 [MSRA-CFW](MSRA-CFW: Data Set of Celebrity Faces on the Web - Microsoft Research)。 202,792 images and 1,583 subjects。
5。 [MegaFace Dataset](MegaFace) 1 Million Faces for Recognition at Scale
690,572 unique people
6。 [FaceScrub](vintage - resources)。 A Dataset With Over 100,000 Face Images of 530 People。
7。 [FDDB](FDDB : Main)。Face Detection and Data Set Benchmark。 5k images。
8。 [AFLW](ICG - Research)。Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization。 25k images。
9。 [AFW](Face Detection Matlab Code)。 Annotated Faces in the Wild。 ~1k images。
10。[3D Mask Attack Dataset](3D Mask Attack Dataset)。 76500 frames of 17 persons using Kinect RGBD with eye positions (Sebastien Marcel)
11。 [Audio-visual database for face and speaker recognition](MOBIO - DDP)。Mobile Biometry MOBIO
http://www。
mobioproject。org/
12。 [BANCA face and voice database](The BANCA Database)。 Univ of Surrey
13。 [Binghampton Univ 3D static and dynamic facial expression database](
http://www。
cs。binghamton。edu/~liju
n/Research/3DFE/3DFE_Analysis。html
)。 (Lijun Yin, Peter Gerhardstein and teammates)
14。 [The BioID Face Database](BioID Face Database | Dataset for Face Detection | facedb - BioID)。 BioID group
15。 [Biwi 3D Audiovisual Corpus of Affective Communication](ETHZ - Computer Vision Lab:)。 1000 high quality, dynamic 3D scans of faces, recorded while pronouncing a set of English sentences。
16。 [Cohn-Kanade AU-Coded Expression Database](The Affect Analysis Group at Pittsburgh)。 500+ expression sequences of 100+ subjects, coded by activated Action Units (Affect Analysis Group, Univ。 of Pittsburgh。
17。 [CMU/MIT Frontal Faces ](CBCL SOFTWARE)。 Training set: 2,429 faces, 4,548 non-faces; Test set: 472 faces, 23,573 non-faces。
18。 [AT&T Database of Faces](The Database of Faces) 400 faces of 40 people (10 images per people)
Trained Model
1。 [openface](cmusatyalab/openface)。 Face recognition with Google‘s FaceNet deep neural network using Torch。
2。 [VGG-Face](VGG Face Descriptor)。 VGG-Face CNN descriptor。 Impressed embedding loss。
3。 [SeetaFace Engine](seetaface/SeetaFaceEngine)。 SeetaFace Engine is an open source C++ face recognition engine, which can run on CPU with no third-party dependence。
4。 [Caffe-face](ydwen/caffe-face) - Caffe Face is developed for face recognition using deep neural networks。
5。 [Norm-Face](happynear/NormFace) - Norm Face, finetuned from [center-face](ydwen/caffe-face) and [Light-CNN](AlfredXiangWu/face_verification_experiment)
6。 [VGG-Face2]VGG-Face 2Dataset
Software
1。 [OpenCV](OpenCV library)。 With some trained face detector models。
2。 [dlib](dlib C++ Library - Machine Learning)。 Dlib implements a state-of-the-art of face Alignment algorithm。
3。 [ccv](liuliu/ccv)。 With a state-of-the-art frontal face detector
4。 [libfacedetection](ShiqiYu/libfacedetection)。 A binary library for face detection in images。
5。 [SeetaFaceEngine](seetaface/SeetaFaceEngine)。 An open source C++ face recognition engine。
Frameworks
1。 [Caffe](Caffe | Deep Learning Framework)
2。 [Torch7](torch/torch7)
3。 [Theano](Welcome - Theano 1。0。0 documentation)
4。 [cuda-convnet](
https://
code。google。com/p/cuda-
convnet/
)
5。 [MXNET](apache/incubator-mxnet)
6。 [Tensorflow](tensorflow)
7。 [tiny-dnn](tiny-dnn/tiny-dnn)
Miscellaneous
1。 [faceswap](matthewearl/faceswap) Face swapping with Python, dlib, and OpenCV
2。 [Facial Keypoints Detection](Facial Keypoints Detection | Kaggle) Competition on Kaggle。
3。 [An implementation of Face Alignment at 3000fps via Local Binary Features](freesouls/face-alignment-at-3000fps)
layout: post
category: deep_learning
title: Face Recognition
date: 2015-10-09
Papers
DeepID
Deep Learning Face Representation from Predicting 10,000 Classes
intro: CVPR 2014
paper:
http://
mmlab。ie。cuhk。edu。hk/pd
f/YiSun_CVPR14。pdf
github:
https://
github。com/stdcoutzyx/D
eepID_FaceClassify
DeepID2
Deep Learning Face Representation by Joint Identification-Verification
paper:
http://
papers。nips。cc/paper/54
16-analog-memories-in-a-balanced-rate-based-network-of-e-i-neurons
基於Caffe的DeepID2實現
1。
http://www。
miaoerduo。com/deep-lear
ning/%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
2。
http://www。
miaoerduo。com/deep-lear
ning/%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
3。
http://www。
miaoerduo。com/deep-lear
ning/%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
DeepID2+
Deeply learned face representations are sparse, selective, and robust
arxiv:
http://
arxiv。org/abs/1412。1265
video:
http://
research。microsoft。com/
apps/video/?id=260023
mirror:
http://
pan。baidu。com/s/1boufl3
x
MobileID
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/mo
bile-id
DeepFace
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/2
0141126/MingYang。pdf
github:
https://
github。com/RiweiChen/De
epFace
Deep Face Recognition
intro: BMVC 2015
paper:
http://www。
robots。ox。ac。uk/~vgg/pu
blications/2015/Parkhi15/parkhi15。pdf
homepage:
http://www。
robots。ox。ac。uk/~vgg/so
ftware/vgg_face/
github(Keras):
https://
github。com/rcmalli/kera
s-vggface
FaceNet
FaceNet: A Unified Embedding for Face Recognition and Clustering
intro: Google Inc。 CVPR 2015
arxiv:
http://
arxiv。org/abs/1503。0383
2
github(Tensorflow):
https://
github。com/davidsandber
g/facenet
github(Caffe):
https://
github。com/hizhangp/tri
plet
Real time face detection and recognition
intro: Real time face detection and recognition base on opencv/tensorflow/mtcnn/facenet
github:
https://
github。com/shanren7/rea
l_time_face_recognition
Targeting Ultimate Accuracy: Face Recognition via Deep Embedding
intro: CVPR 2015
arxiv:
http://
arxiv。org/abs/1506。0731
0
Learning Robust Deep Face Representation
arxiv:
https://
arxiv。org/abs/1507。0484
4
A Light CNN for Deep Face Representation with Noisy Labels
arxiv:
https://
arxiv。org/abs/1511。0268
3
github:
https://
github。com/AlfredXiangW
u/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
Triplet Probabilistic Embedding for Face Verification and Clustering
intro: Oral Paper in BTAS 2016; NVIDIA Best paper Award
arxiv:
https://
arxiv。org/abs/1604。0541
7
github(Keras):
https://
github。com/meownoid/fac
e-identification-tpe
Recurrent Regression for Face Recognition
arxiv:
http://
arxiv。org/abs/1607。0699
9
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/mxn
et_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。0524
6
VIPLFaceNet: An Open Source Deep Face Recognition SDK
keywords: VIPLFaceNet / SeetaFace Engine
arxiv:
http://
arxiv。org/abs/1609。0389
2
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/Se
etaFaceEngine
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。0897
6
Hybrid Deep Learning for Face Verification
intro: TPAMI 2016。 CNN+RBM
paper:
http://www。
ee。cuhk。edu。hk/~xgwang/
papers/sunWTpami16。pdf
Towards End-to-End Face Recognition through Alignment Learning
intro: Tsinghua University
arxiv:
https://
arxiv。org/abs/1701。0717
4
Multi-Task Convolutional Neural Network for Face Recognition
arxiv:
https://
arxiv。org/abs/1702。0471
0
NormFace: L2 Hypersphere Embedding for Face Verification
arxiv:
https://
arxiv。org/abs/1704。0636
9
github:
https://
github。com/happynear/No
rmFace
SphereFace: Deep Hypersphere Embedding for Face Recognition
intro: CVPR 2017
arxiv:
http://
wyliu。com/papers/LiuCVP
R17。pdf
github:
https://
github。com/wy1iu/sphere
face
demo:
http://
v-wb。youku。com/v_show/i
d_XMjk3NTc1NjMxMg==。html
L2-constrained Softmax Loss for Discriminative Face Verification
https://
arxiv。org/abs/1703。0950
7
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。0624
7
Enhancing Convolutional Neural Networks for Face Recognition with Occlusion Maps and Batch Triplet Loss
https://
arxiv。org/abs/1707。0792
3
Model Distillation with Knowledge Transfer in Face Classification, Alignment and Verification
https://
arxiv。org/abs/1709。0292
9
Improving Heterogeneous Face Recognition with Conditional Adversarial Networks
https://
arxiv。org/abs/1709。0284
8
Face Sketch Matching via Coupled Deep Transform Learning
intro: ICCV 2017
arxiv:
https://
arxiv。org/abs/1710。0291
4
Additive Margin Softmax for Face Verification
keywords: additive margin Softmax (AM-Softmax),
arxiv:
https://
arxiv。org/abs/1801。0559
9
github:
https://
github。com/happynear/AM
Softmax
Face Recognition via Centralized Coordinate Learning
https://
arxiv。org/abs/1801。0567
8
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
arxiv:
https://
arxiv。org/abs/1801。0769
8
github:
https://
github。com/deepinsight/
insightface
CosFace: Large Margin Cosine Loss for Deep Face Recognition
https://
arxiv。org/abs/1801。0941
4
Ring loss: Convex Feature Normalization for Face Recognition
intro: CVPR 2018
arxiv:
https://
arxiv。org/abs/1803。0013
0
Pose-Robust Face Recognition via Deep Residual Equivariant Mapping
intro: CVPR 2018。 CUHK & SenseTime Research
arxiv:
https://
arxiv。org/abs/1803。0083
9
Video Face Recognition
Attention-Set based Metric Learning for Video Face Recognition
https://
arxiv。org/abs/1704。0380
5
SeqFace: Make full use of sequence information for face recognitio
arxiv:
https://
arxiv。org/abs/1803。0652
4
github:
https://
github。com/huangyangyu/
SeqFace
Facial Point / Landmark Detection
Deep Convolutional Network Cascade for Facial Point Detection
homepage:
http://
mmlab。ie。cuhk。edu。hk/ar
chive/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/pr
ojects/TCDCN。html
paper:
http://
personal。ie。cuhk。edu。hk
/~ccloy/files/eccv_2014_deepfacealign。pdf
github(Matlab):
https://
github。com/zhzhanp/TCDC
N-face-alignment
A Recurrent Encoder-Decoder Network for Sequential Face Alignment
intro: ECCV 2016 oral
project page:
https://
sites。google。com/site/x
ipengcshomepage/eccv2016
arxiv:
https://
arxiv。org/abs/1608。0547
7
slides:
https://
drive。google。com/file/d
/0B-FLp_bljv_1OTVrMF9OM21IbW8/view
github:
https://
github。com/xipeng13/rec
urrent-face-alignment
RED-Net: A Recurrent Encoder-Decoder Network for Video-based Face Alignment
intro: IJCV
arxiv:
https://
arxiv。org/abs/1801。0606
6
Detecting facial landmarks in the video based on a hybrid framework
arxiv:
http://
arxiv。org/abs/1609。0644
1
Deep Constrained Local Models for Facial Landmark Detection
arxiv:
https://
arxiv。org/abs/1611。0865
7
Effective face landmark localization via single deep network
arxiv:
https://
arxiv。org/abs/1702。0271
9
A Convolution Tree with Deconvolution Branches: Exploiting Geometric Relationships for Single Shot Keypoint Detection
https://
arxiv。org/abs/1704。0188
0
Deep Alignment Network: A convolutional neural network for robust face alignment
intro: CVPRW 2017
arxiv:
https://
arxiv。org/abs/1706。0178
9
gihtub:
https://
github。com/MarekKowalsk
i/DeepAlignmentNetwork
Joint Multi-view Face Alignment in the Wild
https://
arxiv。org/abs/1708。0602
3
FacePoseNet: Making a Case for Landmark-Free Face Alignment
https://
arxiv。org/abs/1708。0751
7
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks
https://
arxiv。org/abs/1711。0675
3
Brute-Force Facial Landmark Analysis With A 140,000-Way Classifier
intro: AAAI 2018
arxiv:
https://
arxiv。org/abs/1802。0177
7
github:
https://
github。com/mtli/BFFL
Style Aggregated Network for Facial Landmark Detection
intro: CVPR 2018
arxiv:
https://
arxiv。org/abs/1803。0410
8
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。0558
8
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/clmtr
ackr
blog:
http://
auduno。com/post/6188827
7175/fitting-faces
demo:
http://
auduno。github。io/clmtra
ckr/examples/facesubstitution。html
demo:
http://
auduno。github。io/clmtra
ckr/face_deformation_video。html
demo:
http://
auduno。github。io/clmtra
ckr/examples/clm_emotiondetection。html
demo:
http://
auduno。com/post/8421458
7523/twisting-faces
DeepLogo
intro: A brand logo recognition system using deep convolutional neural networks。
github:
https://
github。com/satojkovic/D
eepLogo
Deep-Leafsnap
intro: LeafSnap replicated using deep neural networks to test accuracy compared to traditional computer vision methods。
github:
https://
github。com/sujithv28/De
ep-Leafsnap
FaceVerification: An Experimental Implementation of Face Verification, 96.8% on LFW
github:
https://
github。com/happynear/Fa
ceVerification
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/o
penface/
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/TadasBaltrus
aitis/OpenFace
Resources
Face-Resources
github:
https://
github。com/betars/Face-
Resources
Created by ruyiwei on 10/04/2018。