Face Recognition Algorithm Based on Attribute-Driven Loss Function

Shen Li; Hansong Su; Gaohua Liu; Huihua Wu; Meng Wang

doi:10.3788/LOP56.241505

[1] Li J N, Zhang B H. Face recognition by feature matching fusion combined with improved convolutional neural network[J]. Laser & Optoelectronics Progress, 55, 101504(2018).

[2] Hadsell R, Chopra S. LeCun Y. Dimensionality reduction by learning an invariant mapping. [C]∥2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR'06), June 17-22, 2006, New York, NY, USA. New York: IEEE(2006).

[3] Schroff F, Kalenichenko D, Philbin J. FaceNet: a unified embedding for face recognition and clustering. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 815-823(2015).

[4] Ranjan R, Castillo C D. -06-07)[2019-04-24]. https: ∥arxiv., org/abs/1703, 09507(2017).

[5] Wen Y D, Zhang K P, Li Z F et al. A discriminative feature learning approach for deep face recognition[M]. ∥Leibe B, Matas J, Sebe N,et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9911, 499-515(2016).

[6] Liu W Y, Wen Y D, Yu Z D et al. SphereFace: deep hypersphere embedding for face recognition. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 6738-6746(2017).

[7] Xing E P, Ng A Y, Jordan M I et al. Distance metric learning with application to clustering with side-information. [C]∥Advances in Neural Information Processing Systems, December 8-13, 2003, Vancouver and Whistler, British Columbia, Canada. Canada: NIPS, 521-528(2003).

[8] Hernandez M, Choi J, Medioni G. Near laser-scan quality 3-D face reconstruction from a low-quality depth stream[J]. Image and Vision Computing, 36, 61-69(2015). http://dl.acm.org/citation.cfm?id=2784641

[9] Sohn K. Improved deep metric learning with multi-class N-pair loss objective. [C]∥Advances in Neural Information Processing Systems, December 5-10, 2016, Barcelona, Spain. Canada: NIPS, 1857-1865(2016).

[10] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. [C]∥Advances in Neural Information Processing Systems, December 3-6, 2012, Lake Tahoe, Nevada, United States. Canada: NIPS, 1097-1105(2012).

[11] Rudd E M, Günther M, Boult T E. MOON: a mixed objective optimization network for the recognition of facial attributes[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9909, 19-35(2016).

[12] Huang G B, Learned-Miller E. Labeled faces in the wild: updates and new reporting procedures: University of Massachusetts, Amherst Technical Report UM-CS-2014-003[R]. Boston: University of Massachusetts(2014).

[13] Kemelmacher-Shlizerman I, Seitz S M, Miller D et al. The MegaFace benchmark: 1 million faces for recognition at scale. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 4873-4882(2016).

[14] Yang H X, Liu J, Zhang M J et al. Face recognition algorithm based on orthogonal gradient difference local directional pattern[J]. Laser & Optoelectronics Progress, 55, 041008(2018).

[15] Zhang K P, Zhang Z P, Li Z F et al. Joint face detection and alignment using multitask cascaded convolutional networks[J]. IEEE Signal Processing Letters, 23, 1499-1503(2016).

[16] Szegedy C, Ioffe S, Vanhoucke V et al. Inception-v4, inception-ResNet and the impact of residual connections on learning. [C]∥Thirty-First AAAI Conference on Artificial Intelligence, February 4-10, 2017, Hilton, San Francisco Union Square. USA: AAAI, 4278-4284(2017).

[17] Sengupta S, Chen J C, Castillo C et al. Frontal to profile face verification in the wild. [C]∥2016 IEEE Winter Conference on Applications of Computer Vision (WACV),March 7-10, 2016, Lake Placid, NY, USA. New York: IEEE, 16051830(2016).

[18] Moschoglou S, Papaioannou A, Sagonas C et al. AgeDB: the first manually collected, in-the-wild age database. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 1997-2005(2017).