Web-scale training for face identification

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 07-12-June-2015, Issue , 2015, Pages 2746-2754

  Taigman, Yaniv ^a   Yang, Ming ^a   Ranzato, Marc'Aurelio ^a   Wolf, Lior ^b  

^a FACEBOOK AI RESEARCH   (United States)

^b TEL AVIV UNIVERSITY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BENCHMARKING; COMPUTER VISION; LEARNING SYSTEMS; PATTERN RECOGNITION;

CONVOLUTIONAL NETWORKS; FACE IDENTIFICATION; MACHINE LEARNING METHODS; OFF-THE-SHELF SYSTEMS; PERFORMANCE SATURATION; RECOGNITION ACCURACY; STATE OF THE ART; TRANSFER LEARNING;

FACE RECOGNITION;

EID: 84959194885     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7298891     Document Type: Conference Paper

References (27)

1. L. Best-Rowden, H. Han, C. Otto, B. Klare, and A. K. Jain. Unconstrained face recognition: Identifying a person of interest from a media collection. IEEE Transactions on Information Forensics and Security, 2014
2. X. Cao, D. Wipf, F. Wen, G. Duan, and J. Sun. A practical transfer learning algorithm for face verification. In Int'l Conf. on Computer Vision (ICCV), 2013
3. D. Chen, X. Cao, F. Wen, and J. Sun. Blessing of dimensionality: High-dimensional feature and its efficient compression for face verification. In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2013
4. G. E. Dahl, T. N. Sainath, and G. E. Hinton. Improving deep neural networks for LVCSR using rectified linear units and dropout. In ICASSP, 2013
5. C. Dubout and F. Fleuret. Adaptive sampling for large scale boosting. Journal of Machine Learning Re-search, 15:1431-1453, 2014
6. fbcunn Deep Learning CUDA Extensions from Facebook AI Research. https://github. com/facebook/fbcunn, 2014
7. P. J. Grother, G. W. Quinn, and P. J. Phillips. Report on the evaluation of 2D still-image face recognition algorithms. NIST Multiple Biometrics Evaluation (MBE), 2010
8. G. E. Hinton, S. Osindero, and Y.-W. Teh. A fast learning algorithm for deep belief nets. Neural Computa-tion, 2006
9. G. B. Huang and E. Learned-Miller. Labeled faces in the wild: Updates and new reporting procedures. UMCS-2014-003, 2014
10. G. B. Huang, M. Ramesh, T. Berg, and E. Learnedmiller. Labeled faces in the wild: A database for studying face recognition in unconstrained environments. In ECCV Workshop on Faces in Real-life Im-ages, 2008
11. J. C. Klontz and A. K. Jain. A case study of automated face recognition: The boston marathon bombings suspects. IEEE Computer, 2013
12. A. Krizhevsky. One weird trick for parallelizing convolutional neural networks. arXiv:1404. 5997, 2014
13. A. Krizhevsky, I. Sutskever, and G. Hinton. ImageNet classification with deep convolutional neural networks. In Advances in neural information process-ing systems (NIPS), 2012
14. N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar. Attribute and simile classifiers for face verification. In Int'l Conf. on Computer Vision (ICCV), 2009
15. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient based learning applied to document recognition. Proc. IEEE, 1998
16. T. Malisiewicz, A. Gupta, and A. A. Efros. Ensemble of exemplar-SVMs for object detection and beyond. In Int'l Conf. on Computer Vision (ICCV), 2011
17. D. Rumelhart, G. Hinton, and R. Williams. Learning representations by back-propagating errors. Nature, 1986
18. Y. Sun, X. Wang, and X. Tang. Hybrid deep learning for computing face similarities. In Int'l Conf. on Computer Vision (ICCV), 2013
19. Y. Sun, X. Wang, and X. Tang. Deep learning face representation by joint identification-verification. arXiv:1406. 4773, 2014
20. Y. Sun, X. Wang, and X. Tang. Deep learning face representation from predicting 10,000 classes. In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014
21. C. Szegedy,W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus. Intriguing properties of neural networks. arXiv:1312. 6199, 2013
22. Y. Taigman, M. Yang, M. Ranzato, and L. Wolf. Deep-Face: Closing the gap to human-level performance in face verification. In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014
23. P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2001
24. J. Weston, S. Bengio, and N. Usunier. WSABIE: Scaling up to large vocabulary image annotation. In Int'l Joint Conf. on Artificial Intelligence (IJCAI), 2011
25. D. Yi, Z. Lei, S. Liao, and S. Z. Li. Learning face representation from scratch. arXiv:1411. 7923, 2014
26. J. Yosinski, J. Clune, Y. Bengio, and H. Lipson. How transferable are features in deep neural networks? In Advances in neural information processing systems (NIPS), 2014
27. M. Zeiler and R. Fergus. Visualizing and understanding convolutional networks. In European Conf. Com-puter Vision (ECCV), 2014.