Fetching the paper…
Reading the bibliography…
In this paper we address the following question, given a face representation, how many identities can it resolve? In other words, what is the capacity of the face representation? A scientific basis for estimating the capacity of a given face representation will not only benefit the evaluation and comparison of different representation methods, but will also establish an upper bound on the scalability of an automatic face recognition system.
J. B. Kruskal, “Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis,” Psychometrika , vol. 29, no. 1, pp. 1–27, 1964
1964
Earlier work this paper cites.
I. T. Jolliffe, “Principal component analysis and factor analysis,” in Principal Component Analysis . Springer, 1986, pp. 115–128
1986
Earlier work this paper cites.
D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Cognitive Modeling , vol. 5, no. 3, p. 1, 1988
1988
Earlier work this paper cites.
M. A. Turk and A. P. Pentland, “Face recognition using eigenfaces,” in CVPR , 1991
1991
Earlier work this paper cites.
S. T. Roweis and L. K. Saul, “Nonlinear dimensionality reduction by locally linear embedding,” Science , vol. 290, no. 5500, pp. 2323–2326, 2000
2000
Earlier work this paper cites.
J. B. Tenenbaum, V. De Silva, and J. C. Langford, “A global geometric framework for nonlinear dimensionality reduction,” Science , vol. 290, no. 5500, pp. 2319–2323, 2000
2000
Earlier work this paper cites.
S. Pankanti, S. Prabhakar, and A. K. Jain, “On the individuality of fingerprints,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 24, no. 8, pp. 1010–1025, 2002
2002
Earlier work this paper cites.
M. Belkin and P. Niyogi, “Laplacian eigenmaps for dimensionality reduction and data representation,” Neural Computation , vol. 15, no. 6, pp. 1373–1396, 2003
2003
Earlier work this paper cites.
N. A. Schmid and J. A. O’Sullivan, “Performance prediction methodology for biometric systems using a large deviations approach,” IEEE Transactions on Signal Processing , vol. 52, no. 10, pp. 3036–3045, 2004
2004
Earlier work this paper cites.
P. Viola and M. J. Jones, “Robust real-time face detection,” International Journal of Computer Vision , vol. 57, no. 2, pp. 137–154, 2004
2004
Earlier work this paper cites.
N. A. Schmid, M. V. Ketkar, H. Singh, and B. Cukic, “Performance analysis of iris-based identification system at the matching score level,” IEEE Transactions on Information Forensics and Security , vol. 1, no. 2, pp. 154–168, 2006
2006
Earlier work this paper cites.
G. E. Hinton and R. R. Salakhutdinov, “Reducing the dimensionality of data with neural networks,” Science , vol. 313, no. 5786, pp. 504–507, 2006
2006
Earlier work this paper cites.
C. E. Rasmussen and C. K. Williams, Gaussian Processes for Machine Learning . MIT Press Cambridge, 2006, vol. 1
2006
Earlier work this paper cites.
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller, “Labeled faces in the wild: A database for studying face recognition in unconstrained environments,” Technical Report 07-49, University of Massachusetts, Amherst, Tech. Rep., 2007
2007
Earlier work this paper cites.
P. Wang, Q. Ji, and J. L. Wayman, “Modeling and predicting face recognition system performance based on analysis of similarity scores,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 29, no. 4, pp. 665–670, 2007
2007
Earlier work this paper cites.
Y. Zhu, S. C. Dass, and A. K. Jain, “Statistical models for assessing the individuality of fingerprints,” IEEE Transactions on Information Forensics and Security , vol. 2, no. 3, pp. 391–401, 2007
2007
Earlier work this paper cites.
J. Bhatnagar and A. Kumar, “On estimating performance indices for biometric identification,” Pattern Recognition , vol. 42, no. 9, pp. 1803–1815, 2009
2009
Earlier work this paper cites.
A. Der Kiureghian and O. Ditlevsen, “Aleatory or epistemic? does it matter?” Structural Safety , vol. 31, no. 2, pp. 105–112, 2009
2009
Cited alongside, same era.
A. Adler, R. Youmaran, and S. Loyka, “Towards a measure of biometric feature information,” Pattern Analysis and Applications , vol. 12, no. 3, pp. 261–270, 2009
2009
Cited alongside, same era.
P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol, “Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion,” Journal of Machine Learning Research , vol. 11, no. Dec, pp. 3371–3408, 2010
2010
Cited alongside, same era.
L. Bottou, “Large-scale machine learning with stochastic gradient descent,” in Proceedings of COMPSTAT’2010 . Springer, 2010, pp. 177–186
2010
Cited alongside, same era.
R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification . John Wiley & Sons, 2012
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in CVPR , 2015
2015
Later among the works it cites.
——, “A theoretically grounded application of dropout in recurrent neural networks,” in NIPS , 2016
2016
Later among the works it cites.
J. Daugman, “Information theory and the iriscode,” IEEE Transactions on Information Forensics and Security , vol. 11, no. 2, pp. 400–409, 2016
2016
Later among the works it cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in CVPR , 2016
2016
Later among the works it cites.
K. Zhang, Z. Zhang, Z. Li, and Y. Qiao, “Joint face detection and alignment using multitask cascaded convolutional networks,” IEEE Signal Processing Letters , vol. 23, no. 10, pp. 1499–1503, 2016
2016
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2012
Cited alongside, same era.
T. M. Cover and J. A. Thomas, Elements of Information Theory . John Wiley & Sons, 2012
2012
Cited alongside, same era.
J. Ba and R. Caruana, “Do deep nets really need to be deep?” in NIPS , 2014
2014
Cited alongside, same era.
2014
Cited alongside, same era.
2014
Cited alongside, same era.
S. Liao, Z. Lei, D. Yi, and S. Z. Li, “A benchmark study of large-scale unconstrained face recognition,” in IJCB , 2014
2014
Cited alongside, same era.
C. Lu and X. Tang, “Surpassing human-level face verification performance on lfw with gaussianface,” in AAAI , 2015
2015
Cited alongside, same era.
F. Schroff, D. Kalenichenko, and J. Philbin, “Facenet: A unified embedding for face recognition and clustering,” in CVPR , 2015
2015
Cited alongside, same era.
Later among the works it cites.
2016
Later among the works it cites.
I. Kemelmacher-Shlizerman, S. M. Seitz, D. Miller, and E. Brossard, “The megaface benchmark: 1 million faces for recognition at scale,” in CVPR , 2016
2016
Later among the works it cites.
W. Liu, Y. Wen, Z. Yu, M. Li, B. Raj, and L. Song, “Sphereface: Deep hypersphere embedding for face recognition,” in IEEE Conference on Computer Vision and Pattern Recognition , 2017
2017
Closest in time.
A. Kendall and Y. Gal, “What uncertainties do we need in bayesian deep learning for computer vision?” in NIPS , 2017
2017
Closest in time.
C. Whitelam, E. Taborsky, A. Blanton, B. Maze, J. Adams, T. Miller, N. Kalka, A. K. Jain, J. A. Duncan, K. Allen et al. , “IARPA janus benchmark-b face dataset,” in CVPRW , 2017
2017
Closest in time.
D. Wang, C. Otto, and A. K. Jain, “Face search at scale: 80 million gallery,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 39, no. 6, pp. 1122 – 1136, 2017
2017
Closest in time.
B. Maze, J. Adams, J. A. Duncan, N. Kalka, T. Miller, C. Otto, A. K. Jain, W. T. Niggel, J. Anderson, J. Cheney et al. , “Iarpa janus benchmark–c: Face dataset and protocol,” in International Conference on Biometrics , 2018
2018
Closest in time.
X. Wu, R. He, Z. Sun, and T. Tan, “A light cnn for deep face representation with noisy labels,” IEEE Transactions on Information Forensics and Security , vol. 13, no. 11, pp. 2884–2896, 2018
2018
Closest in time.
2018
Closest in time.
W. Xie, L. Shen, and A. Zisserman, “Comparator networks,” arXiv preprint arXiv:1807.11440 , 2018
2018
Closest in time.
L. Best-Rowden and A. K. Jain, “Longitudinal study of automatic face recognition,” IEEE transactions on pattern analysis and machine intelligence , vol. 40, no. 1, pp. 148–162, 2018
2018
Closest in time.
S. Gong, V. N. Boddeti, and A. K. Jain, “Deepmds: Non-linear projection of deep representations,” in IEEE Conference on Computer Vision and Pattern Recognition , 2019
2019
Closest in time.