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Previous generations of face recognition algorithms differ in accuracy for images of different races (race bias).
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G. Givens, J. R. Beveridge, B. A. Draper, P. Grother, and P. J. Phillips, “How features of the human face affect recognition: a statistical comparison of three face recognition algorithms,” in Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. , vol. 2. IEEE, 2004, pp. II–II
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D. J. Kelly, P. C. Quinn, A. M. Slater, K. Lee, L. Ge, and O. Pascalis, “The other-race effect develops during infancy: Evidence of perceptual narrowing,” Psychological Science , vol. 18, no. 12, pp. 1084–1089, 2007
2007
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J. R. Beveridge, G. H. Givens, P. J. Phillips, B. A. Draper, and Y. M. Lui, “Focus on quality, predicting frvt 2006 performance,” in 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition . IEEE, 2008, pp. 1–8
2008
Cited alongside, same era.
J. R. Beveridge, G. H. Givens, P. J. Phillips, and B. A. Draper, “Factors that influence algorithm performance in the face recognition grand challenge,” Computer Vision and Image Understanding , vol. 113, no. 6, pp. 750–762, 2009
2009
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P. J. Phillips, W. T. Scruggs, A. J. O’Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “FRVT 2006 and ICE 2006 large-scale results,” IEEE Trans. PAMI , vol. 32, no. 5, pp. 831–846, 2010
2010
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P. J. Phillips, F. Jiang, A. Narvekar, J. Ayyad, and A. J. O’Toole, “An other-race effect for face recognition algorithms,” ACM Transactions on Applied Perception (TAP) , vol. 8, no. 2, p. 14, 2011
2011
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K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 770–778
2016
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D. S. Y. Tham, J. G. Bremner, and D. Hay, “The other-race effect in children from a multiracial population: a cross-cultural comparison,” Journal of experimental child psychology , vol. 155, pp. 128–137, 2017
2017
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A. J. O’Toole and P. J. Phillips, “Five principles for crowd-source experiments in face recognition,” in 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) . IEEE, 2017, pp. 735–741
2017
Later among the works it cites.
2017
Later among the works it cites.
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P. J. Phillips, J. R. Beveridge, B. A. Draper, G. Givens, A. J. O’Toole, D. S. Bolme, J. Dunlop, Y. M. Lui, H. Sahibzada, and S. Weimer, An introduction to the good, the bad, & the ugly face recognition challenge problem . IEEE, 2011
2011
Cited alongside, same era.
C. M. Bukach, J. Cottle, J. Ubiwa, and J. Miller, “Individuation experience predicts other-race effects in holistic processing for both caucasian and black participants,” Cognition , vol. 123, no. 2, pp. 319–324, 2012
2012
Cited alongside, same era.
B. F. Klare, M. J. Burge, J. C. Klontz, R. W. V. Bruegge, and A. K. Jain, “Face recognition performance: Role of demographic information,” IEEE Transactions on Information Forensics and Security , vol. 7, no. 6, pp. 1789–1801, 2012
2012
Cited alongside, same era.
H. Wechsler, J. P. Phillips, V. Bruce, F. F. Soulié, and T. S. Huang, Face recognition: From theory to applications . Springer Science & Business Media, 2012, vol. 163
2012
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A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in neural information processing systems , 2012, pp. 1097–1105
2012
Cited alongside, same era.
A. J. O’Toole, P. J. Phillips, X. An, and J. Dunlop, “Demographic effects on estimates of automatic face recognition performance,” Image and Vision Computing , vol. 30, no. 3, pp. 169–176, 2012
2012
Cited alongside, same era.
G. Anzures, D. J. Kelly, O. Pascalis, P. C. Quinn, A. M. Slater, X. De Viviés, and K. Lee, “Own-and other-race face identity recognition in children: The effects of pose and feature composition.” Developmental psychology , vol. 50, no. 2, p. 469, 2014
2014
Cited alongside, same era.
P. J. Phillips and A. J. O’Toole, “Comparison of human and computer performance across face recognition experiments,” Image and Vision Computing , vol. 32, no. 1, pp. 74–85, 2014
2014
Cited alongside, same era.
P. J. Phillips, “A cross benchmark assessment of a deep convolutional neural network for face recognition,” in 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) . IEEE, 2017, pp. 705–710
2017
Later among the works it cites.
P. J. Phillips, A. N. Yates, Y. Hu, C. A. Hahn, E. Noyes, K. Jackson, J. G. Cavazos, G. Jeckeln, R. Ranjan, S. Sankaranarayanan et al. , “Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms,” Proceedings of the National Academy of Sciences , vol. 115, no. 24, pp. 6171–6176, 2018
2018
Later among the works it cites.
K. Krishnapriya, K. Vangara, M. C. King, V. Albiero, and K. Bowyer, “Characterizing the variability in face recognition accuracy relative to race,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019
2019
Closest in time.
P. Grother, M. Ngan, and K. Hanaoka, “Face recognition vendor test (frvt) part 3: Demographic effects,” National Institute of Standards and Technology , 2019
2019
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C. M. Cook, J. J. Howard, Y. B. Sirotin, J. L. Tipton, and A. R. Vemury, “Demographic effects in facial recognition and their dependence on image acquisition: An evaluation of eleven commercial systems,” IEEE Transactions on Biometrics, Behavior, and Identity Science , vol. 1, no. 1, pp. 32–41, 2019
2019
Closest in time.
J. J. Howard, Y. Sirotin, and A. Vemury, “The effect of broad and specific demographic homogeneity on the imposter distributions and false match rates in face recognition algorithm performance,” in Proc. 10-th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS , 2019
2019
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K. Bowyer, “Why face recognition accuracy varies due to race,” Biometric Technology Today , vol. 2019, no. 8, pp. 8–11, 2019
2019
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R. Ranjan, A. Bansal, J. Zheng, H. Xu, J. Gleason, B. Lu, A. Nanduri, J.-C. Chen, C. D. Castillo, and R. Chellappa, “A fast and accurate system for face detection, identification, and verification,” IEEE Transactions on Biometrics, Behavior, and Identity Science , vol. 1, no. 2, pp. 82–96, 2019
2019
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2019
Closest in time.
K. Krishnapriya, V. Albiero, K. Vangara, M. C. King, and K. W. Bowyer, “Issues related to face recognition accuracy varying based on race and skin tone,” IEEE Transactions on Technology and Society , 2020
2020
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