Recover Canonical-View Faces in the Wild with Deep Neural Networks

Keywords

Artificial intelligence, Computer science, Canonical correlation, Face (sociological concept), Convolutional neural network

References

• Improving neural networks by preventing co-adaptation of feature detectorsGeoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky — 2012
• Face recognition with learning-based descriptorZhimin Cao, Qi Yin, Xiaoou Tang — 2010
• Deep Learning Face Representation from Predicting 10,000 ClassesYi Sun, Xiaogang Wang, Xiaoou Tang — 2014
• Face Hallucination: Theory and PracticeCe Liu, Heung‐Yeung Shum, William T. Freeman — 2007
• Learning hierarchical representations for face verification with convolutional deep belief networksGuoyang Huang, Honglak Lee, Erik Learned-Miller — 2012
• Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters.John Daugman — 1985
• An associate-predict model for face recognitionQi Yin, Xiaoou Tang, Jian Sun — 2011
• Tom-vs-Pete Classifiers and Identity-Preserving Alignment for Face VerificationThomas Berg, Peter N. Belhumeur — 2012
• A Practical Transfer Learning Algorithm for Face VerificationXudong Cao, David Wipf, Fang Wen — 2013
• Fast High Dimensional Vector Multiplication Face RecognitionOren Barkan, Jonathan Weill, Lior Wolf — 2013
• Surpassing Human-Level Face Verification Performance on LFW with GaussianFaceChaochao Lu, Xiaoou Tang — 2014
• Blessing of Dimensionality: High-Dimensional Feature and Its Efficient Compression for Face VerificationDong Chen, Xudong Cao, Fang Wen — 2013
• A Compositional and Dynamic Model for Face AgingJinli Suo, Song-Chun Zhu, Shiguang Shan — 2010
• Convolutional deep belief networks for scalable unsupervised learning of hierarchical representationsHonglak Lee, Roger Grosse, Rajesh Ranganath — 2009
• Hybrid Deep Learning for Face VerificationYi Sun, Xiaogang Wang, Xiaoou Tang — 2013
• Viewing Real-World Faces in 3DTal Hassner — 2013
• Eigenfaces for RecognitionMatthew Turk, Alex Pentland — 1991
• Energy Normalization for Pose-Invariant Face Recognition Based on MRF Model Image MatchingShervin Rahimzadeh Arashloo, Josef Kittler — 2011
• Automatic eyeglasses removal from face imagesChenyu Wu, Ce Liu, Heung-Yueng Shum — 2004
• Face Photo-Sketch Synthesis and RecognitionXiaogang Wang, Xiaoou Tang — 2009

Cited by

• A Comprehensive Survey on Pose-Invariant Face RecognitionChangxing Ding, Dacheng Tao — 2015
• Learning Deep Representation for Face Alignment with Auxiliary AttributesZhanpeng Zhang, Ping Luo, Chen Change Loy — 2014
• Deep learning and face recognition: the state of the artStephen Balaban — 2015
• Naive-Deep Face Recognition: Touching the Limit of LFW Benchmark or Not?Erjin Zhou, Zhimin Cao, Qi Yin — 2015
• Single Sample Face Recognition via Learning Deep Supervised AutoencodersShenghua Gao, Yuting Zhang, Kui Jia — 2015
• Effective face frontalization in unconstrained imagesTal Hassner, Shai Har-El, Eran Paz — 2014
• High-fidelity Pose and Expression Normalization for face recognition in the wildXiangyu Zhu, Zhen Lei, Junjie Yan — 2015
• Hierarchical-PEP model for real-world face recognitionHaoxiang Li, Gang Hua — 2015
• Deep Learning Face Representation from Predicting 10,000 ClassesYi Sun, Xiaogang Wang, Xiaoou Tang — 2014
• Switchable Deep Network for Pedestrian DetectionPing Luo, Yonglong Tian, Xiaogang Wang — 2014
• FaceNet: A unified embedding for face recognition and clusteringFlorian Schroff, Dmitry Kalenichenko, James Philbin — 2015
• Surpassing Human-Level Face Verification Performance on LFW with GaussianFaceChaochao Lu, Xiaoou Tang — 2014
• DeepID3: Face Recognition with Very Deep Neural NetworksYi Sun, Ding Liang, Xiaogang Wang — 2015
• Stacked Face De-Noising Auto Encoders for Expression-Robust Face RecognitionChathurdara Sri Nadith Pathirage, Ling Li, Wanquan Liu — 2015
• A comparison of deep multilayer networks and Markov random field matching models for face recognition in the wildShervin Rahimzadeh Arashloo — 2016
• Hybrid sensing face detection and recognitionMingyuan Zhou, Haiting Lin, Jingyi Yu — 2015
• Pose-Aware Face Recognition in the WildIacopo Masi, Stephen Rawls, Gérard Medioni — 2016
• Weakly-supervised deep self-learning for face recognitionBinghui Chen, Weihong Deng — 2016
• Robust face recognition via transfer learning for robot partnerNoel Nuo Wi Tay, János Botzheim, Chu Kiong Loo — 2014
• Face Model Compression by Distilling Knowledge from NeuronsPing Luo, Zhenyao Zhu, Ziwei Liu — 2016

Related papers

• Understanding Canonical Correlation through the General Linear Model and Principal ComponentsKeith E. Muller — 1982
• ON GENERALIZED CANONICAL CORRELATION ANALYSISMichel van de Velden — 2011
• Interpretation of Canonical Discriminant Functions, Canonical Variates, and Principal ComponentsAlvin C. Rencher — 1992
• Simultaneous canonical correlation analysis with invariant canonical loadingsФэй Гу, Hao Wu — 2017
• Identification of linear systems via canonical correlation analysisKemal Gürkan Toker, Yakup Özkazanç — 2013
• Functional canonical analysis for square integrable stochastic processesGuozhong He, Hans‐Georg Müller, Jane-Ling Wang — 2003
• Face Detection and RecognitionAnil K. Jain — 2004
• On the Use of Correlations to Interpret Canonical FunctionsAlvin C. Rencher — 1988
• Analysis of the effects of image transformation, template selection, and partial information on face recognition with time-varying expressions for homeland security applicationsIliana V. Voynichka, Dalila B. Megherbi — 2013
• An Analysis on Face Recognition using Principal Component Analysis ApproachWenyu Zhang, Burra Venkata Durga Kumar, Kelvin J. A. Ooi — 2022