本文转自：https://github.com/betars/Face-Resources

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. .A work from Facebook.
2. .A work from Google.
3. . Dlib implements the algorithm.

Datasets

1. . 10,575 subjects and 494,414 images
2. .13,000 images and 5749 subjects
3.  202,599 images and 10,177 subjects. 5 landmark locations, 40 binary attributes.
4. . 202,792 images and 1,583 subjects.
5.  1 Million Faces for Recognition at Scale 690,572 unique people
6. . A Dataset With Over 100,000 Face Images of 530 People.
7. .Face Detection and Data Set Benchmark. 5k images.
8. .Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization. 25k images.
9. . Annotated Faces in the Wild. ~1k images. 10.. 76500 frames of 17 persons using Kinect RGBD with eye positions (Sebastien Marcel)
10. .Mobile Biometry MOBIO 
11. . Univ of Surrey
12. . (Lijun Yin, Peter Gerhardstein and teammates)
13. . BioID group
14. . 1000 high quality, dynamic 3D scans of faces, recorded while pronouncing a set of English sentences.
15. . 500+ expression sequences of 100+ subjects, coded by activated Action Units (Affect Analysis Group, Univ. of Pittsburgh.
16. . Training set: 2,429 faces, 4,548 non-faces; Test set: 472 faces, 23,573 non-faces.
17.  400 faces of 40 people (10 images per people)

Trained Model

1. . Face recognition with Google's FaceNet deep neural network using Torch.
2. . VGG-Face CNN descriptor. Impressed embedding loss.
3. . SeetaFace Engine is an open source C++ face recognition engine, which can run on CPU with no third-party dependence.
4.  - Caffe Face is developed for face recognition using deep neural networks.

Tutorial

1. . Shiguan Shan, Xiaogang Wang, and Ming yang.

Software

1. . With some trained face detector models.
2. . Dlib implements a state-of-the-art of face Alignment algorithm.
3. . With a state-of-the-art frontal face detector
4. . A binary library for face detection in images.
5. . An open source C++ face recognition engine.

Frameworks

Miscellaneous

1.  Face swapping with Python, dlib, and OpenCV
2.  Competition on Kaggle.

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Created by betars on 27/10/2015.