Face Recognition with Local Binary Patterns, Computer vision-eccv 2004, pp.469-481, 2004. ,
DOI : 10.1007/978-3-540-24670-1_36
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.6851
Recognition of blurred faces using Local Phase Quantization, 2008 19th International Conference on Pattern Recognition, 2008. ,
DOI : 10.1109/ICPR.2008.4761847
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.5028
Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection, pp.711-720, 1997. ,
Review and implementation of high-dimensional local binary patterns and its application to face recognition, 2014. ,
Bayesian Face Revisited: A Joint Formulation, ECCV. 2012 ,
DOI : 10.1007/978-3-642-33712-3_41
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.306.6417
Blessing of Dimensionality: High-Dimensional Feature and Its Efficient Compression for Face Verification, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.389
Training invariant support vector machines, Machine Learning, pp.161-190, 2002. ,
Multi-directional multilevel dual-cross patterns for robust face recognition. arXiv preprint arXiv, pp.1401-5311, 2014. ,
DOI : 10.1109/tpami.2015.2462338
URL : http://arxiv.org/pdf/1401.5311
Cascaded Collaborative Regression for Robust Facial Landmark Detection Trained Using a Mixture of Synthetic and Real Images With Dynamic Weighting, IEEE Transactions on Image Processing, vol.24, issue.11, pp.3425-3440, 2015. ,
DOI : 10.1109/TIP.2015.2446944
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.81
URL : http://arxiv.org/abs/1311.2524
Is that you? Metric learning approaches for face identification, 2009 IEEE 12th International Conference on Computer Vision, 2009. ,
DOI : 10.1109/ICCV.2009.5459197
URL : https://hal.archives-ouvertes.fr/inria-00439290
Effective face frontalization in unconstrained images, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. ,
DOI : 10.1109/CVPR.2015.7299058
URL : http://arxiv.org/abs/1411.7964
Deep Residual Learning for Image Recognition, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2016.90
URL : http://arxiv.org/pdf/1512.03385
When Face Recognition Meets with Deep Learning: An Evaluation of Convolutional Neural Networks for Face Recognition, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW), 1504. ,
DOI : 10.1109/ICCVW.2015.58
Labeled faces in the wild: a database for studying face recognition in unconstrained environments, 2007. ,
Synthetic data and artificial neural networks for natural scene text recognition, 2014. ,
Aggregating local descriptors into a compact image representation, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. ,
DOI : 10.1109/CVPR.2010.5540039
Properties and performance of a center/surround retinex, IEEE Transactions on Image Processing, vol.6, issue.3, pp.451-462, 1997. ,
DOI : 10.1109/83.557356
NIR-VIS heterogeneous face recognition via cross-spectral joint dictionary learning and reconstruction, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp.141-150, 2015. ,
DOI : 10.1109/CVPRW.2015.7301308
Recent advances in visual and infrared face recognition???a review, Computer Vision and Image Understanding, vol.97, issue.1, pp.103-135, 2005. ,
DOI : 10.1016/j.cviu.2004.04.001
ImageNet classification with deep convolutional neural networks, Communications of the ACM, vol.60, issue.6, 2012. ,
DOI : 10.1162/neco.2009.10-08-881
URL : http://dl.acm.org/ft_gateway.cfm?id=3065386&type=pdf
The CASIA NIR-VIS 2.0 Face Database, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.348-353, 2013. ,
DOI : 10.1109/CVPRW.2013.59
Targeting ultimate accuracy: Face recognition via deep embedding, 2015. ,
Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004. ,
DOI : 10.1023/B:VISI.0000029664.99615.94
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.4931
Learning compact binary face descriptor for face recognition. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2015. ,
DOI : 10.1109/tpami.2015.2408359
Do We Really Need to Collect Millions of Faces for Effective Face Recognition?, 2016. ,
DOI : 10.1109/CVPR.2013.454
Megaface: A million faces for recognition at scale. arXiv preprint, 2015. ,
A survey on heterogeneous face recognition: Sketch, infra-red, 3D and low-resolution, Image and Vision Computing, vol.56, 2016. ,
DOI : 10.1016/j.imavis.2016.09.001
URL : http://arxiv.org/pdf/1409.5114
Semantic pose using deep networks trained on synthetic rgb-d. arXiv preprint, 2015. ,
DOI : 10.1109/iccv.2015.95
URL : http://arxiv.org/pdf/1508.00835
Deep Face Recognition, Procedings of the British Machine Vision Conference 2015, 2015. ,
DOI : 10.5244/C.29.41
Transformation Pursuit for Image Classification, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.466
URL : https://hal.archives-ouvertes.fr/hal-00979464
Poisson image editing, In ACM Transactions on Graphics, 2003. ,
From image-level to pixel-level labeling with Convolutional Networks, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2015.7298780
URL : http://arxiv.org/abs/1411.6228
MoCap-guided data augmentation for 3D pose estimation in the wild, NIPS, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01389486
On rendering synthetic images for training an object detector, Computer Vision and Image Understanding, vol.137, 2015. ,
DOI : 10.1016/j.cviu.2014.12.006
URL : http://arxiv.org/pdf/1411.7911
On rendering synthetic images for training an object detector, Computer Vision and Image Understanding, vol.137, pp.24-37, 2015. ,
DOI : 10.1016/j.cviu.2014.12.006
URL : http://arxiv.org/pdf/1411.7911
Image Classification with the Fisher Vector: Theory and Practice, International Journal of Computer Vision, vol.73, issue.2, pp.222-245, 2013. ,
DOI : 10.1007/s11263-006-9794-4
Heterogeneous face recognition with CNNs, ECCV TASK-CV Workshop, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01367455
FaceNet: A unified embedding for face recognition and clustering, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2015.7298682
URL : http://arxiv.org/abs/1503.03832
Real-time human pose recognition in parts from single depth images, Communications of the ACM, vol.56, issue.1, pp.116-124, 2013. ,
DOI : 10.1145/2398356.2398381
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.211.403
The CMU Pose, Illumination, and Expression (PIE) database, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition, 2002. ,
DOI : 10.1109/AFGR.2002.1004130
URL : http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.16.1577&rep=rep1&type=pdf
Fisher Vector Faces in the Wild, Procedings of the British Machine Vision Conference 2013, 2013. ,
DOI : 10.5244/C.27.8
Two-stream convolutional networks for action recognition in videos, NIPS, 2014. ,
Very deep convolutional networks for large-scale image recognition, 2015. ,
Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views, 2015 IEEE International Conference on Computer Vision (ICCV), 2015. ,
DOI : 10.1109/ICCV.2015.308
ACTIVE: Activity Concept Transitions in Video Event Classification, 2013 IEEE International Conference on Computer Vision, 2013. ,
DOI : 10.1109/ICCV.2013.453
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.649.3302
Deep learning face representation by joint identification-verification, Advances in Neural Information Processing Systems, pp.1988-1996, 2014. ,
DOI : 10.1109/iccv.2013.188
URL : http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Sun_Hybrid_Deep_Learning_2013_ICCV_paper.pdf
Deepid3: Face recognition with very deep neural networks, 2015. ,
Hybrid deep learning for face verification, ICCV, 2013. ,
DOI : 10.1109/iccv.2013.188
URL : http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Sun_Hybrid_Deep_Learning_2013_ICCV_paper.pdf
Deep Learning Face Representation from Predicting 10,000 Classes, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.1891-1898, 2014. ,
DOI : 10.1109/CVPR.2014.244
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.646.8205
Deeply learned face representations are sparse, selective, and robust, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. ,
DOI : 10.1109/CVPR.2015.7298907
URL : http://arxiv.org/abs/1412.1265
Going deeper with convolutions, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2015.7298594
URL : http://arxiv.org/abs/1409.4842
DeepFace: Closing the Gap to Human-Level Performance in Face Verification, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.220
DeepFace: Closing the Gap to Human-Level Performance in Face Verification, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.1701-1708, 2014. ,
DOI : 10.1109/CVPR.2014.220
Face recognition using eigenfaces, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.586-591, 1991. ,
DOI : 10.1109/CVPR.1991.139758
Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion, Journal of Machine Learning Research, vol.11, pp.3371-3408, 2010. ,
Distance metric learning for large margin nearest neighbor classification, JMLR, vol.10, pp.207-244, 2009. ,
Material Classification Based on Training Data Synthesized Using a BTF Database, ECCV, 2014. ,
DOI : 10.1007/978-3-319-10578-9_11
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.665.8015
Normalization of Face Illumination Based on Large-and Small-Scale Features, IEEE Transactions on Image Processing, vol.20, issue.7, pp.1807-1821, 2011. ,
DOI : 10.1109/TIP.2010.2097270
Shared representation learning for heterogeneous face recognition, International Conference on Automatic Face and Gesture Recognition, 2015. ,
Learning face representation from scratch, 2014. ,
Sketch-a-Net: A Deep Neural Network that Beats Humans, International Journal of Computer Vision, vol.52, issue.12, 2016. ,
DOI : 10.1109/CVPR.2013.387
Visualizing and Understanding Convolutional Networks, ECCV, 2014. ,
DOI : 10.1007/978-3-319-10590-1_53
URL : http://arxiv.org/abs/1311.2901
Facial Landmark Detection by Deep Multi-task Learning, ECCV, 2014. ,
DOI : 10.1007/978-3-319-10599-4_7
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.681.4854
Face alignment across large poses: A 3d solution. arXiv preprint, 2015. ,
DOI : 10.1109/cvpr.2016.23
URL : http://arxiv.org/abs/1511.07212
High-fidelity pose and expression normalization for face recognition in the wild, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.787-796, 2015. ,