Do We Really Need to Collect Millions of Faces for Effective Face Recognition?
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-46454-1_35
Reference47 articles.
1. AbdAlmageed, W., Wu, Y., Rawls, S., Harel, S., Hassner, T., Masi, I., Choi, J., Leksut, J., Kim, J., Natarajan, P., Nevatia, R., Medioni, G.: Face recognition using deep multi-pose representations. In: Winter Conference on Applications of Computer Vision (2016)
2. Baltrusaitis, T., Robinson, P., Morency, L.P.: Constrained local neural fields for robust facial landmark detection in the wild. In: Proceedings of the International Conference on Computer Vision Workshops (2013)
3. Chatfield, K., Simonyan, K., Vedaldi, A., Zisserman, A.: Return of the devil in the details: Delving deep into convolutional nets. In: Proceedings of the British Machine Vision Conference (2014)
4. Chen, J.C., Sankaranarayanan, S., Patel, V.M., Chellappa, R.: Unconstrained face verification using fisher vectors computed from frontalized faces. In: International Conference on Biometrics: Theory, Applications and Systems (2015)
5. Chen, J.C., Patel, V.M., Chellappa, R.: Unconstrained face verification using deep cnn features. In: Winter Conference on Applications of Computer Vision (2016)
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