Fetching the paper…
Reading the bibliography…
In this paper, we propose a conceptually simple and geometrically interpretable objective function, i.e.
Labeled faces in the wild: A database for studying face recognition in unconstrained environments
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller · 2007
Earlier work this paper cites.
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
Earlier work this paper cites.
A benchmark study of large-scale unconstrained face recognition
S. Liao, Z. Lei, D. Yi, and S. Z. Li · 2014
Earlier work this paper cites.
Deep learning face representation by joint identification-verification
Y. Sun, Y. Chen, X. Wang, and X. Tang · 2014
Earlier work this paper cites.
Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
Earlier work this paper cites.
Learning face representation from scratch
D. Yi, Z. Lei, S. Liao, and S. Z. Li · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2015
Earlier work this paper cites.
Deep face recognition
O. M. Parkhi, A. Vedaldi, and A. Zisserman · 2015
Earlier work this paper cites.
Facenet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
The megaface benchmark: 1 million faces for recognition at scale
I. Kemelmacher-Shlizerman, S. M. Seitz, D. Miller, and E. Brossard · 2016
Cited alongside, same era.
Large-margin softmax loss for convolutional neural networks
W. Liu, Y. Wen, Z. Yu, and M. Yang · 2016
Cited alongside, same era.
A discriminative feature learning approach for deep face recognition
Y. Wen, K. Zhang, Z. Li, and Y. Qiao · 2016
Cited alongside, same era.
Joint face detection and alignment using multitask cascaded convolutional networks
K. Zhang, Z. Zhang, Z. Li, and Y. Qiao · 2016
Cited alongside, same era.
Sphereface: Deep hypersphere embedding for face recognition
W. Liu, Y. Wen, Z. Yu, M. Li, B. Raj, and L. Song · 2017
Later among the works it cites.
Deep hyperspherical learning
W. Liu, Y.-M. Zhang, X. Li, Z. Yu, B. Dai, T. Zhao, and L. Song · 2017
Later among the works it cites.
Rethinking feature discrimination and polymerization for large-scale recognition
Y. Liu, H. Li, and X. Wang · 2017
Later among the works it cites.
Regularizing neural networks by penalizing confident output distributions
G. Pereyra, G. Tucker, J. Chorowski, Ł. Kaiser, and G. Hinton · 2017
Later among the works it cites.
L2-constrained softmax loss for discriminative face verification
R. Ranjan, C. D. Castillo, and R. Chellappa · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Soft-margin softmax for deep classification
X. Liang, X. Wang, Z. Lei, S. Liao, and S. Z. Li · 2017
Cited alongside, same era.
Focal loss for dense object detection
T.-Y. Lin, P. Goyal, R. Girshick, K. He, and P. Dollár · 2017
Cited alongside, same era.
Normface: L2 hypersphere embedding for face verification
F. Wang, X. Xiang, J. Cheng, and A. L. Yuille · 2017
Later among the works it cites.
Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017
H. Xiao, K. Rasul, and R. Vollgraf · 2017
Later among the works it cites.
Feature incay for representation regularization
Y. Yuan, K. Yang, and C. Zhang · 2017
Later among the works it cites.