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Face recognition performance evaluation has traditionally focused on one-to-one verification, popularized by the Labeled Faces in the Wild dataset for imagery and the YouTubeFaces dataset for videos.
Large-scale learning with svm and convolutional for generic object categorization
Huang, F., LeCun, Y.: · 2006
Earlier work this paper cites.
Labeled faces in the wild: A database for studying face recognition in unconstrained environments
Huang, G., Ramesh, M., Berg, T., Learned-Miller, E.: · 2007
Earlier work this paper cites.
Liblinear: A library for large linear classification
Fan, R., Chang, K., Hsieh, C., Wang, X., Lin, C.: · 2008
Earlier work this paper cites.
The one-shot similarity kernel
Wolf, L., Hassner, T., Taigman, Y.: · 2009
Earlier work this paper cites.
A survey on transfer learning
Pan, S.J., Yang, Q.: · 2010
Earlier work this paper cites.
Face recognition in unconstrained videos with matched background similarity
Wolf, L., Hassner, T., Maoz, I.: · 2011
Earlier work this paper cites.
Ensemble of exemplar-svms for object detection and beyond
Malisiewicz, T., Gupta, A., Efros, A.: · 2011
Earlier work this paper cites.
Effective unconstrained face recognition by combining multiple descriptors and learned background statistics
Wolf, L., Hassner, T., Taigman, Y.: · 2011
Earlier work this paper cites.
Parallelized stochastic gradient descent
Zinkevich, M., et al: · 2011
Earlier work this paper cites.
Bayesian face revisited: A joint formulation
Chen, D., Cao, X., Wang, L., Wen, F., Sun, J.: · 2012
Earlier work this paper cites.
Deep learning with linear support vector machines
Tang, Y.: · 2013
Earlier work this paper cites.
Regularization of neural network using dropconnect
Wan, L., Zeiler, M., Zhang, S., LeCun, Y., Fergus, R.: · 2013
Earlier work this paper cites.
DeepFace: Closing the gap to human-level performance in face verification
Taigman, Y., Yang, M., Ranzato, M., Wolf, L.: · 2014
Earlier work this paper cites.
DeepID3: Face recognition with very deep neural networks
Sun, Y., Liang, D., Wang, X., Tang., X.: · 2014
Cited alongside, same era.
Unconstrained face recognition: Identifying a person of interest from a media collection
Best-Rowden, L., Han, H., Otto, C., Klare, B., Jain, A.K.: · 2014
Cited alongside, same era.
Face recognition vendor test (frvt): Performance of face identification algorithms
Grother, P., Ngan, M.: · 2014
Cited alongside, same era.
Cnn features off-the-shelf: An astounding baseline for recognition
Razavian, A.S., Azizpour, H., Sullivan, J., Carlsson, S.: · 2014
Cited alongside, same era.
A compact and discriminative face track descriptor
Parkhi, O.M., Simonyan, K., Vedaldi, A., Zisserman, A.: · 2014
Cited alongside, same era.
One millisecond face alignment with an ensemble of regression trees
Surpassing human-level face verification performance on LFW with GaussianFace
Lu, C., Tang, X.: · 2015
Later among the works it cites.
Human and algorithm performance on the pasc face recognition challenge
Phillips, J., Hill, M., Swindle, J., O’Toole, A.: · 2015
Later among the works it cites.
Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2015
Later among the works it cites.
Going deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: · 2015
Later among the works it cites.
When face recognition meets with deep learning: an evaluation of convolutional neural networks for face recognition
Hu, G., Yang, Y., Yi, D., Kittler, J., Christmas, W., Li, S.Z., Hospedales, T.: · 2015
Later among the works it cites.
An end-to-end system for unconstrained face verification with deep convolutional neural networks
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Kazemi, V., Sullivan, J.: · 2014
Cited alongside, same era.
Learning face representation from scratch
Yi, D., Lei, Z., Liao, S., Li, S.: · 2014
Cited alongside, same era.
Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus benchmark A
Klare, B., Klein, B., Taborsky, E., Blanton, A., Cheney, J., Allen, K., Grother, P., Mah, A., Jain, A.: · 2015
Cited alongside, same era.
Deep face recognition
Parkhi, O., Vedaldi, A., Zisserman, A.: · 2015
Cited alongside, same era.
FaceNet: A unified embedding for face recognition and clustering
Schroff, F., Kalenichenko, D., Philbin, J.: · 2015
Cited alongside, same era.
Web-scale training for face identification
Y. Taigman, M. Yang, M.R., Wolf, L.: · 2015
Cited alongside, same era.
Deeply learned face representations are sparse, selective, and robust
Sun, Y., Wang, X., Tang., X.: · 2015
Cited alongside, same era.
Chen, J., Ranjan, R., Kumar, A., Chen, C., Patel, V., Chellappa, R.: · 2015
Later among the works it cites.
Three viewpoints toward exemplar svm
Kobayashi, T.: · 2015
Later among the works it cites.
Face search at scale: 80 million gallery
Wang, D., Otto, C., Jain, A.: · 2015
Later among the works it cites.
Triplet similarity embedding for face verification
Sankaranarayanan, S., Alavi, A., Chellappa, R.: · 2016
Closest in time.
Unconstrained face verification using deep CNN features
J. Chen, V.P., Chellappa, R.: · 2016
Closest in time.
Face recognition using deep multi-pose representations
AbdAlmageed, W., Wu, Y., Rawls, S., Harel, S., Hassner, T., Masi, I., Choi, J., Lekust, J., Kim, J., Natarajan, P., Nevatia, R., Medioni, G.: · 2016
Closest in time.
One-to-many face recognition with bilinear CNNs
RoyChowdry, A., Lin, T., Maji, S., Learned-Miller, E.: · 2016
Closest in time.