Improving multiview face detection with multi-task deep convolutional neural networks

2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014

Volumn , Issue , 2014, Pages 1036-1041

  Zhang, Cha ^a   Zhang, Zhengyou ^a  

^a MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORKS;

CONVOLUTIONAL NEURAL NETWORK; DETECTION PERFORMANCE; FACE POSE ESTIMATION; FACIAL LANDMARK; FALSE POSITIVE RATES; MULTI-VIEW FACE DETECTION; MULTITASK LEARNING; STATE-OF-THE-ART METHODS;

FACE RECOGNITION;

EID: 84904682004     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WACV.2014.6835990     Document Type: Conference Paper

References (35)

1. R. Caruana. Multitask Learning. PhD thesis, Carnegie Mellon University, 1997.
2. R. Collobert and J.Weston. A unified architecture for natural language processing: Deep neural networks with multitask learning. In Proc. of ICML, 2008.
3. G. E. Dahl, D. Yu, L. Deng, and A. Acero. Contextdependent pre-Trained deep neural networks for largevocabulary speech recognition. IEEE Transactions on Audio, Speech, and Language Processing, 20(1):30-42, 2012.
4. R. Feraud, O. J. Bernier, J.-E. Viallet, and M. Collobert. A fast and accurate face detector based on neural networks. IEEE Trans. on PAMI, 23(1):42-53, 2001.
5. C. Garcia and M. Delakis. Convolutional face finder: A neural architecture for fast and robust face detection. IEEE Trans. on PAMI, 26(11):1408-1423, 2004.
6. C. Huang, H. Ai, Y. Li, and S. Lao. Vector boosting for rotation invariant multi-view face detection. In Proc. of ICCV, 2005.
7. G. B. Huang, H. Lee, and E. Learned-Miller. Learning hierarchical representations for face verification with convolutional deep belief networks. In Proc. of CVPR, 2012.
8. V. Jain and E. Learned-Miller. FDDB: A benchmark for face detection in unconstrained settings. Technical report, University of Massachusetts, Amherst, UM-CS-2010-009, 2010.
9. V. Jain and E. G. Learned-Miller. Online domain adaptation of a pre-Trained cascade of classifiers. In Proc. of CVPR, 2011.
10. O. Jesorsky, K. Kirchberg, and R. Frischholz. Robust face detection using the hausdorff distance. Audio and Video based Person Authentication-AVBPA 2001, pages 90-95, 2001.
11. F. Jin and S. Sun. Neural network multitask learning for traffic flow forecasting. In Proc. of IJCNN, 2008
12. H. Jin, Q. Liu, H. Lu, and X. Tong. Face detection using improved lbp under bayesian framework. In Third Intl. Conf. on Image and Grahics (ICIG), 2004.
13. M. Jones and P. Viola. Fast multi-view face detection. Technical report, Mitsubishi Electric Research Laboratories, TR2003-96, 2003.
14. A. Krizhevsky, I. Sutskever, and G. Hinton. ImageNet classification with deep convolutional neural networks. In Proc. of NIPS, 2012.
15. H. Li, G. Hua, Z. Lin, J. Brandt, and J. Yang. Probabilistic elastic part model for unsupervised face detector adaptation. In Proc. of ICCV, 2013.
16. J. Li, T. Wang, and Y. Zhang. Face detection using SURF cascade. In ICCV 2011 BeFIT workshop 2011.
17. C. Liu and H.-Y. Shum. Kullback-Leibler boosting. In Proc. Of CVPR, 2003.
18. T. Ojala, M. Pietikainen, and T. Maenpaa. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. on PAMI, 24:971-987, 2002.
19. M. Osadchy, M. L. Miller, and Y. L. Cun. Synergistic face detection and pose estimation with energy-based models. In Proc. of NIPS, 2004.
20. P. J. Phillips, H. Moon, P. J. Rauss, and S. Rizvi. The FERET evaluation methodology for face recognition algorithms. IEEE Trans. on PAMI, 22(10):1090-1104, 2000.
21. X. W. Ping Luo and X. Tang. Hierarchical face parsing via deep learning. In Proc. of IEEE CVPR, 2012
22. A. r. Mohamed, D. Yu, and L. Deng. Investigation of fullsequence training of deep belief networks for speech recognition. In INTERSPEECH, 2010.
23. D. Roth, M.-H. Yang, and N. Ahuja. A SNoW-based face detector. In Proc. of NIPS, 2000.
24. H. A. Rowley, S. Baluja, and T. Kanade. Neural networkbased face detection. In Proc. of CVPR, 1996.
25. P. Sermanet, K. Kavukcuoglu, S. Chintala, and Y. LeCun. Pedestrian detection with unsupervised multi-stage feature learning. In Proc. of CVPR, 2013.
26. X. Shen, Z. Lin, J. Brandt, and Y.Wu. Detecting and aligning faces by image retrieval. In Proc. of CVPR 2013.
27. T. Sim, S. Baker, and M. Bsat. The CMU pose, illumination, and expression database. IEEE Trans. on PAMI, 25(12):1615-1618, 2003.
28. Y. Sun, X. Wang, and X. Tang. Deep convolutional network cascade for facial point detection. In Proc. of CVPR, 2013.
29. P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In Proc. of CVPR, 2001.
30. B. Wu, H. Ai, C. Huang, and S. Lao. Fast rotation invariant multi-view face detection based on real adaboost. In Proc. of IEEE Automatic Face and Gesture Recognition, 2004.
31. R. Xiao, M.-J. Li, and H.-J. Zhang. Robust multipose face detection in images. IEEE Trans. on CSVT, 14(1):31-41, 2004.
32. M.-H. Yang, D. J. Kriegman, and N. Ahuja. Detecting faces in images: A survey. IEEE Trans. on PAMI, 24(1):34-58, 2002.
33. C. Zhang and Z. Zhang. Winner-Take-All multiple category boosting for multi-view face detection. In ECCV Workshop on Face Detection: Where are we, and what next, 2009.
34. C. Zhang and Z. Zhang. A survey of recent advances in face detection. Technical report, Microsoft Research MSR-TR-2010-66, 2010.
35. X. Zhu and D. Ramanan. Face detection, pose estimation, and landmark localization in the wild. In Proc. of CVPR, 2012 .