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The purpose of this page is to curate datasets before putting them on pages like List of datasets for machine learning research.

Dataset Name Brief description Preprocessing Instances Format Default Task Created (updated) Reference Creator
Facial Recognition Technology (FERET) 11338 images of 1199 individuals in different positions and at different times. None. 11,338 Images Classification, facial recognition 2003 [1][2] United States Department of Defense
Pose, Illumination, and Expression (PIE) 41,368 color images of 68 people in 13 different poses. Images labeled with expressions. 41,368 Images, text Classification, facial recognition 2000 [3][4] R. Gross et al.
SCFace Color images of faces at various angles. Location of facial features extracted. Coordinates of features given. 4,160 Images, text Classification, facial recognition 2011 [5][6] M. Grgic et al.
YouTube Faces DB Videos of 1,595 different people gathered from YouTube. Each clip is between 48 and 6,070 frames. Identity of those appearing in videos and descriptors. 3,425 videos Video, text Video classification, facial recognition 2011 [7][8] L. Wolf et al.
Grammatical Facial Expressions Dataset Grammatical Facial Expressions from Brazilian Sign Language. Microsoft Kinect features extracted. 27,965 Text Facial gesture recognition 2014 [9] F. Freitas et al.
CMU Face Images Dataset Images of faces. Each person is photographed multiple times to capture different expressions. Labels and features. 640 Images, Text Facial recognition 1999 [10][11] T. Mitchell
Yale Face Database Faces of 15 individuals in 11 different expressions. Labels of expressions. 165 Images Facial recognition 1997 [12][13] J. Yang et al.
Cohn-Kanade AU-Coded Expression Database Large database of images with labels for expressions. Tracking of certain facial features. 500+ sequences Images, text Facial recognition 2000 [14][15] T. Kanade et al.
FaceScrub Images of public figures scrubbed from image searching. Name and m/f annotation. 107,818 Images, text Facial recognition 2014 [16][17] H. Ng et al.
BioID Face Database Images of faces with eye positions marked. Manually set eye positions. 1521 Images, text Facial recognition 2001 [18][19] BioID
Skin Segmentation Dataset Randomly sampled color values from face images. B, G, R, values extracted. 245,057 Text Segmentation, classification 2012 [20][21] R. Bhatt.
Bosphorus 3D Facial image database. 34 action units and 6 expressions labeled; 24 facial landmarks labeled. 4652

Images, text

Facial recognition, classification 2008 [22][23] A Savran et al.
UOY 3D-Face neutral face, 5 expressions: anger, happiness, sadness, eyes closed, eyebrows raised. labeling. 5250

Images, text

Facial recognition, classification ~2004 [24][25] University of York
CASIA Expressions: Anger, smile, laugh, surprise, closed eyes. None. 4624

Images, text

Facial recognition, classification 2007 [26][27] Institute of Automation, Chinese Academy of Sciences
BU-3DFE neutral face, and 6 expressions: anger, happiness, sadness, surprise, disgust, fear (4 levels). 3D images extracted. None. 2500 Images, text Facial recognition, classification 2006 [28] Binghamton University
Face Recognition Grand Challenge Dataset Up to 22 samples for each subject. Expressions: anger, happiness, sadness, surprise, disgust, puffy. 3D Data. None. 4007 Images, text Facial recognition, classification 2004 [29][30] National Institute of Standards and Technology
Gavabdb Up to 61 samples for each subject. Expressions neutral face, smile, frontal accentuated laugh, frontal random gesture. 3D images. None. 549 Images, text Facial recognition, classification 2008 [31][32] King Juan Carlos University
3D-RMA Up to 100 subjects, expressions mostly neutral. Several poses as well. None. 9971 Images, text Facial recognition, classification 2004 [33][34] Royal Military Academy (Belgium)
  1. ^ Phillips, P. Jonathon, et al. "The FERET database and evaluation procedure for face-recognition algorithms." Image and vision computing 16.5 (1998): 295-306.
  2. ^ Wiskott, Laurenz, et al. "Face recognition by elastic bunch graph matching."Pattern Analysis and Machine Intelligence, IEEE Transactions on 19.7 (1997): 775-779.
  3. ^ Sim, Terence, Simon Baker, and Maan Bsat. "The CMU pose, illumination, and expression (PIE) database." Automatic Face and Gesture Recognition, 2002. Proceedings. Fifth IEEE International Conference on. IEEE, 2002.
  4. ^ Schroff, Florian, et al. "Pose, illumination and expression invariant pairwise face-similarity measure via doppelgänger list comparison."Computer Vision (ICCV), 2011 IEEE International Conference on. IEEE, 2011.
  5. ^ Grgic, Mislav, Kresimir Delac, and Sonja Grgic. "SCface–surveillance cameras face database." Multimedia tools and applications 51.3 (2011): 863-879.
  6. ^ Wallace, Roy, et al. "Inter-session variability modelling and joint factor analysis for face authentication." Biometrics (IJCB), 2011 International Joint Conference on. IEEE, 2011.
  7. ^ Schroff, Florian, Dmitry Kalenichenko, and James Philbin. "Facenet: A unified embedding for face recognition and clustering." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
  8. ^ Wolf, Lior, Tal Hassner, and Itay Maoz. "Face recognition in unconstrained videos with matched background similarity." Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on. IEEE, 2011.
  9. ^ de Almeida Freitas, Fernando, et al. "Grammatical Facial Expressions Recognition with Machine Learning." FLAIRS Conference. 2014.
  10. ^ Mitchell, Tom M. "Machine learning. WCB." (1997).
  11. ^ Xiaofeng He and Partha Niyogi. Locality Preserving Projections. NIPS. 2003.
  12. ^ Georghiades, A. "Yale face database." Center for computational Vision and Control at Yale University, http://cvc. yale. edu/projects/yalefaces/yalefa 2 (1997).
  13. ^ Nguyen, Duy, et al. "Real-time face detection and lip feature extraction using field-programmable gate arrays." Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 36.4 (2006): 902-912.
  14. ^ Kanade, Takeo, Jeffrey F. Cohn, and Yingli Tian. "Comprehensive database for facial expression analysis." Automatic Face and Gesture Recognition, 2000. Proceedings. Fourth IEEE International Conference on. IEEE, 2000.
  15. ^ Zeng, Zhihong, et al. "A survey of affect recognition methods: Audio, visual, and spontaneous expressions." Pattern Analysis and Machine Intelligence, IEEE Transactions on 31.1 (2009): 39-58.
  16. ^ Ng, Hong-Wei, and Stefan Winkler. "A data-driven approach to cleaning large face datasets." Image Processing (ICIP), 2014 IEEE International Conference on. IEEE, 2014.
  17. ^ RoyChowdhury, Aruni; Lin, Tsung-Yu; Maji, Subhransu; Learned-Miller, Erik (2015). "One-to-many face recognition with bilinear CNNs". arXiv:1506.01342 [cs.CV].
  18. ^ Jesorsky, Oliver, Klaus J. Kirchberg, and Robert W. Frischholz. "Robust face detection using the hausdorff distance." Audio-and video-based biometric person authentication. Springer Berlin Heidelberg, 2001.
  19. ^ Huang, Gary B., et al. Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Vol. 1. No. 2. Technical Report 07-49, University of Massachusetts, Amherst, 2007.
  20. ^ Bhatt, Rajen B., et al. "Efficient skin region segmentation using low complexity fuzzy decision tree model." India Conference (INDICON), 2009 Annual IEEE. IEEE, 2009.
  21. ^ Lingala, Mounika, et al. "Fuzzy logic color detection: Blue areas in melanoma dermoscopy images." Computerized Medical Imaging and Graphics 38.5 (2014): 403-410.
  22. ^ Maes, Chris, et al. "Feature detection on 3D face surfaces for pose normalisation and recognition." Biometrics: Theory Applications and Systems (BTAS), 2010 Fourth IEEE International Conference on. IEEE, 2010.
  23. ^ Savran, Arman, et al. "Bosphorus database for 3D face analysis." Biometrics and Identity Management. Springer Berlin Heidelberg, 2008. 47-56.
  24. ^ Heseltine, Thomas, Nick Pears, and Jim Austin. "Three-dimensional face recognition: An eigensurface approach." Image Processing, 2004. ICIP'04. 2004 International Conference on. Vol. 2. IEEE, 2004.
  25. ^ Ge, Yun, et al. "3D Novel Face Sample Modeling for Face Recognition."Journal of Multimedia 6.5 (2011): 467-475.
  26. ^ Wang, Yueming, Jianzhuang Liu, and Xiaoou Tang. "Robust 3D face recognition by local shape difference boosting." Pattern Analysis and Machine Intelligence, IEEE Transactions on 32.10 (2010): 1858–1870.
  27. ^ Zhong, Cheng, Zhenan Sun, and Tieniu Tan. "Robust 3D face recognition using learned visual codebook." Computer Vision and Pattern Recognition, 2007. CVPR'07. IEEE Conference on. IEEE, 2007.
  28. ^ Soyel, Hamit, and Hasan Demirel. "Facial expression recognition using 3D facial feature distances." Image Analysis and Recognition. Springer Berlin Heidelberg, 2007. 831-838.
  29. ^ Bowyer, Kevin W., Kyong Chang, and Patrick Flynn. "A survey of approaches and challenges in 3D and multi-modal 3D+ 2D face recognition." Computer vision and image understanding 101.1 (2006): 1-15.
  30. ^ Tan, Xiaoyang, and Bill Triggs. "Enhanced local texture feature sets for face recognition under difficult lighting conditions." Image Processing, IEEE Transactions on 19.6 (2010): 1635–1650.
  31. ^ Mousavi, Mir Hashem, Karim Faez, and Amin Asghari. "Three dimensional face recognition using svm classifier." Computer and Information Science, 2008. ICIS 08. Seventh IEEE/ACIS International Conference on. IEEE, 2008.
  32. ^ Amberg, Brian, Reinhard Knothe, and Thomas Vetter. "Expression invariant 3D face recognition with a morphable model." Automatic Face & Gesture Recognition, 2008. FG'08. 8th IEEE International Conference on. IEEE, 2008.
  33. ^ İrfanoğlu, M. O., Berk Gökberk, and Lale Akarun. "3D shape-based face recognition using automatically registered facial surfaces." Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on. Vol. 4. IEEE, 2004.
  34. ^ Beumier, Charles, and Marc Acheroy. "Face verification from 3D and grey level clues." Pattern recognition letters 22.12 (2001): 1321–1329.
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