Alireza-Akhavan / Deep Face Recognition
Projects that are alternatives of or similar to Deep Face Recognition
Deep Face Recognition using Tensorflow workshop material
(Thursday, August 30, 2018 )
- One-shot & low-shot learning
- Siamese network
- What is metric learning & Face embedding?
- Face Verification and Identification Challanges: Lfw, Megaface
- Facenet Triplet Loss, Center Loss, Sphere Face, Amsoftmax, Arcface
- How align a face with MTCNN Landmarks
Slides:
Slideshare | download pptx
video capture:
Jupyter notebooks:
face Verification with face embedding
face detection and 5 point landmarks with MTCNN
face Identification & Recognition
Face alignment with 5 point landmarks
Important link
facenet pretrained model (Tensorflow)
Sphereface or Angular Softmax (Caffe)
ArcFace (MXNet)
AMSoftmax (Caffe)
Iranian Face Dataset
Datasets
- CASIA WebFace Database. 10,575 subjects and 494,414 images
- Labeled Faces in the Wild.13,000 images and 5749 subjects
- Large-scale CelebFaces Attributes (CelebA) Dataset 202,599 images and 10,177 subjects. 5 landmark locations, 40 binary attributes.
- MSRA-CFW. 202,792 images and 1,583 subjects.
- MegaFace Dataset 1 Million Faces for Recognition at Scale 690,572 unique people
- FaceScrub. A Dataset With Over 100,000 Face Images of 530 People.
- FDDB.Face Detection and Data Set Benchmark. 5k images.
- AFLW.Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization. 25k images.
- AFW. Annotated Faces in the Wild. ~1k images. 10.3D Mask Attack Dataset. 76500 frames of 17 persons using Kinect RGBD with eye positions (Sebastien Marcel)
- Audio-visual database for face and speaker recognition.Mobile Biometry MOBIO http://www.mobioproject.org/
- BANCA face and voice database. Univ of Surrey
- Binghampton Univ 3D static and dynamic facial expression database. (Lijun Yin, Peter Gerhardstein and teammates)
- The BioID Face Database. BioID group
- Biwi 3D Audiovisual Corpus of Affective Communication. 1000 high quality, dynamic 3D scans of faces, recorded while pronouncing a set of English sentences.
- Cohn-Kanade AU-Coded Expression Database. 500+ expression sequences of 100+ subjects, coded by activated Action Units (Affect Analysis Group, Univ. of Pittsburgh.
- CMU/MIT Frontal Faces . Training set: 2,429 faces, 4,548 non-faces; Test set: 472 faces, 23,573 non-faces.
- AT&T Database of Faces 400 faces of 40 people (10 images per people)
Other Face Dataset
Face Detection Dataset
FDDB
paper: http://vis-www.cs.umass.edu/fddb/fddb.pdf
dataset: http://vis-www.cs.umass.edu/fddb/index.html#download
Wider Face
extreme scale
paper: https://arxiv.org/pdf/1511.06523.pdf
dataset: http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/index.html
MAFA
occlusion
paper: http://openaccess.thecvf.com/content_cvpr_2017/papers/Ge_Detecting_Masked_Faces_CVPR_2017_paper.pdf
dataset: http://www.escience.cn/people/geshiming/mafa.html
4k face dataset
hight resolution
paper: https://arxiv.org/pdf/1804.06559.pdf
Unconstrained Face Detection Dataset (UFDD)
different weather
paper: https://arxiv.org/abs/1804.10275
dataset: https://github.com/hezhangsprinter/UFDD
wildest faces
paper: https://arxiv.org/pdf/1805.07566.pdf
Multi-Attribute Labelled Faces (MALF)
paper: http://www.cbsr.ia.ac.cn/faceevaluation/faceevaluation15.pdf
dataset: http://www.cbsr.ia.ac.cn/faceevaluation/#reference
IJB-A Dataset
paper: https://zhaoj9014.github.io/pub/IJBA_1N_report.pdf
dataset: https://www.nist.gov/itl/iad/image-group/ijb-dataset-request-form
Age Estimation Dataset
Adience dataset
dataset: https://talhassner.github.io/home/projects/Adience/Adience-data.html
statistic: Total number of images: 26,580 Total number of subjects: 2,284 Number of age groups: 8 (0-2, 4-6, 8-13, 15-20, 25-32, 38-43, 48-53, 60-) Gender labels: Yes In the wild: Yes Subject labels: Yes
UTK-Face
dataset: https://susanqq.github.io/UTKFace/
APPA-REAL (real and apparent age)
dataset: http://chalearnlap.cvc.uab.es/dataset/26/description/
Face Landmark Detection Dataset
300W
paper: https://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_iccv_2013_300_w.pdf
COFW
occluded to different degrees
paper: https://www.microsoft.com/en-us/research/wp-content/uploads/2013/12/BurgosArtizzuICCV13rcpr.pdf
AFLW
faces with large head pose up to 120◦ for yaw and 90◦ for pitch and roll.
paper: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.384.2988&rep=rep1&type=pdf
dataset: https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/aflw/
WFLW
from wider face dataset
paper: https://arxiv.org/pdf/1805.10483.pdf
dataset: https://wywu.github.io/projects/LAB/WFLW.html
papers:
FaceNet: A Unified Embedding for Face Recognition and Clustering (2015)
A Discriminative Feature Learning Approach for Deep Face Recognition (2016)
SphereFace: Deep Hypersphere Embedding for Face Recognition (2018)
Additive Margin Softmax for Face Verification (2018)
Ring loss: Convex Feature Normalization for Face Recognition(2018)
ArcFace: Additive Angular Margin Loss for Deep Face Recognition (2019)
Deep Face Recognition: A Survey (2019)
source:
https://github.com/jian667/face-dataset
https://github.com/jian667/Face-Resources/