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Diffstat (limited to 'site/datasets')
25 files changed, 773 insertions, 19 deletions
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Sciences,edu,3d89f9b4da3d6fb1fdb33dea7592b5992069a096,citation,https://doi.org/10.1109/CISP-BMEI.2017.8302003,Face recognition based on convolution siamese networks,2017 +86,LFW,lfw,25.01682835,121.53846924,National Taiwan University,edu,e51927b125640bfc47bbf1aa00c3c026748c75bd,citation,http://doi.acm.org/10.1145/2647868.2655015,Automatic Facial Image Annotation and Retrieval by Integrating Voice Label and Visual Appearance,2014 +87,LFW,lfw,1.2962018,103.77689944,National University of Singapore,edu,4e8c608fc4b8198f13f8a68b9c1a0780f6f50105,citation,http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Yang_How_Related_Exemplars_2013_ICCV_paper.pdf,How Related Exemplars Help Complex Event Detection in Web Videos?,2013 +88,LFW,lfw,-27.49741805,153.01316956,University of Queensland,edu,4e8c608fc4b8198f13f8a68b9c1a0780f6f50105,citation,http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Yang_How_Related_Exemplars_2013_ICCV_paper.pdf,How Related Exemplars Help Complex Event Detection in Web Videos?,2013 +89,LFW,lfw,37.4102193,-122.05965487,Carnegie Mellon University,edu,4e8c608fc4b8198f13f8a68b9c1a0780f6f50105,citation,http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Yang_How_Related_Exemplars_2013_ICCV_paper.pdf,How Related Exemplars Help Complex Event Detection in Web Videos?,2013 +90,LFW,lfw,37.5901411,127.0362318,Korea University,edu,ce8db0fe11e7c96d08de561506f9f8f399dabbb2,citation,https://doi.org/10.1109/ICIP.2015.7351677,Weighted sparse representation using a learned distance metric for face recognition,2015 +91,LFW,lfw,1.2962018,103.77689944,National University of Singapore,edu,2836d68c86f29bb87537ea6066d508fde838ad71,citation,http://arxiv.org/pdf/1510.06503v1.pdf,Personalized Age Progression with Aging Dictionary,2015 +92,LFW,lfw,32.0565957,118.77408833,Nanjing University,edu,2836d68c86f29bb87537ea6066d508fde838ad71,citation,http://arxiv.org/pdf/1510.06503v1.pdf,Personalized Age Progression with Aging Dictionary,2015 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University,edu,39f525f3a0475e6bbfbe781ae3a74aca5b401125,citation,http://pdfs.semanticscholar.org/39f5/25f3a0475e6bbfbe781ae3a74aca5b401125.pdf,Deep Joint Face Hallucination and Recognition,2016 +259,LFW,lfw,40.00229045,116.32098908,Tsinghua University,edu,88cd4209db62a34d9cba0b9cbe9d45d1e57d21e5,citation,https://pdfs.semanticscholar.org/88cd/4209db62a34d9cba0b9cbe9d45d1e57d21e5.pdf,Runtime Neural Pruning,2017 +260,LFW,lfw,-34.9181706,-56.1665725,"Universidad de la República, Uruguay",edu,3b75681f0162752865d85befd8b15e7d954ebfe6,citation,https://doi.org/10.1109/CLEI.2014.6965097,Evaluation of a face recognition system performance's variation on a citizen passports database,2014 +261,LFW,lfw,45.5039761,-73.5749687,McGill University,edu,ed9d11e995baeec17c5d2847ec1a8d5449254525,citation,https://pdfs.semanticscholar.org/ed9d/11e995baeec17c5d2847ec1a8d5449254525.pdf,Efficient Gender Classification Using a Deep LDA-Pruned Net,2017 +262,LFW,lfw,40.0044795,116.370238,Chinese Academy of Sciences,edu,21d1315761131ea6b3e2afe7a745b606341616fd,citation,https://pdfs.semanticscholar.org/21d1/315761131ea6b3e2afe7a745b606341616fd.pdf,Generative Adversarial Network with Spatial Attention for Face Attribute Editing,2018 +263,LFW,lfw,39.9082804,116.2458527,University of Chinese Academy of Sciences,edu,21d1315761131ea6b3e2afe7a745b606341616fd,citation,https://pdfs.semanticscholar.org/21d1/315761131ea6b3e2afe7a745b606341616fd.pdf,Generative Adversarial Network with Spatial Attention for Face Attribute Editing,2018 +264,LFW,lfw,40.0044795,116.370238,Chinese Academy of Sciences,edu,13a994d489c15d440c1238fc1ac37dad06dd928c,citation,http://pdfs.semanticscholar.org/13a9/94d489c15d440c1238fc1ac37dad06dd928c.pdf,Learning Discriminant Face Descriptor for Face Recognition,2012 +265,LFW,lfw,33.776033,-84.39884086,Georgia Institute of Technology,edu,96f0e7416994035c91f4e0dfa40fd45090debfc5,citation,https://arxiv.org/pdf/1803.01260.pdf,Unsupervised Learning of Face Representations,2018 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Learning for Unconstrained Face Processing,2014 +278,LFW,lfw,42.718568,-84.47791571,Michigan State University,edu,051f03bc25ec633592aa2ff5db1d416b705eac6c,citation,http://www.cse.msu.edu/biometrics/Publications/Face/LiaoJain_PartialFR_AlignmentFreeApproach_ICJB11.pdf,Partial face recognition: An alignment free approach,2011 +279,LFW,lfw,31.846918,117.29053367,Hefei University of Technology,edu,f6e6b4d0b7c16112dcb71ff502033a2187b1ec9b,citation,https://doi.org/10.1109/TMM.2015.2476657,Understanding Blooming Human Groups in Social Networks,2015 +280,LFW,lfw,29.58333105,-98.61944505,University of Texas at San Antonio,edu,f6e6b4d0b7c16112dcb71ff502033a2187b1ec9b,citation,https://doi.org/10.1109/TMM.2015.2476657,Understanding Blooming Human Groups in Social Networks,2015 +281,LFW,lfw,1.2962018,103.77689944,National University of Singapore,edu,f6e6b4d0b7c16112dcb71ff502033a2187b1ec9b,citation,https://doi.org/10.1109/TMM.2015.2476657,Understanding Blooming Human Groups in Social Networks,2015 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Intervention,2013 +286,LFW,lfw,28.3656193,75.5834953,"Central Electronics Research Institute, Pilani, India",edu,1aeef2ab062c27e0dbba481047e818d4c471ca57,citation,https://doi.org/10.1109/ICACCI.2015.7275860,Analyzing impact of image scaling algorithms on viola-jones face detection framework,2015 +287,LFW,lfw,34.0224149,-118.28634407,University of Southern California,edu,d6ae7941dcec920d5726d50d1b1cdfe4dde34d35,citation,http://dl.acm.org/citation.cfm?id=31310887,Avatar digitization from a single image for real-time rendering,2017 +288,LFW,lfw,28.54632595,77.27325504,Indian Institute of Technology Delhi,edu,fba95853ca3135cc52a4b2bc67089041c2a9408c,citation,https://pdfs.semanticscholar.org/fba9/5853ca3135cc52a4b2bc67089041c2a9408c.pdf,Disguised Faces in the Wild,2018 +289,LFW,lfw,39.2899685,-76.62196103,University of Maryland,edu,fba95853ca3135cc52a4b2bc67089041c2a9408c,citation,https://pdfs.semanticscholar.org/fba9/5853ca3135cc52a4b2bc67089041c2a9408c.pdf,Disguised Faces in the Wild,2018 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shot similarity,2011 +294,LFW,lfw,39.9082804,116.2458527,University of Chinese Academy of Sciences,edu,ac2881bdf7b57dc1672a17b221d68a438d79fce8,citation,https://arxiv.org/pdf/1806.08472.pdf,Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization,2018 +295,LFW,lfw,46.0501558,14.46907327,University of Ljubljana,edu,69adbfa7b0b886caac15ebe53b89adce390598a3,citation,https://arxiv.org/pdf/1805.10938.pdf,Face hallucination using cascaded super-resolution and identity priors,2018 +296,LFW,lfw,41.70456775,-86.23822026,University of Notre Dame,edu,69adbfa7b0b886caac15ebe53b89adce390598a3,citation,https://arxiv.org/pdf/1805.10938.pdf,Face hallucination using cascaded super-resolution and identity priors,2018 +297,LFW,lfw,-33.8840504,151.1992254,University of Technology,edu,8686b15802529ff8aea50995ef14079681788110,citation,https://doi.org/10.1109/TNNLS.2014.2376936,Deformed Graph Laplacian for Semisupervised Learning,2015 +298,LFW,lfw,31.20081505,121.42840681,Shanghai Jiao Tong University,edu,8686b15802529ff8aea50995ef14079681788110,citation,https://doi.org/10.1109/TNNLS.2014.2376936,Deformed Graph Laplacian for Semisupervised Learning,2015 +299,LFW,lfw,35.9020448,139.93622009,University of Tokyo,edu,9f131b4e036208f2402182a1af2a59e3c5d7dd44,citation,http://dl.acm.org/citation.cfm?id=3206038,Face Retrieval Framework Relying on User's Visual Memory,2018 +300,LFW,lfw,33.8898728,130.70856205,Waseda University,edu,9f131b4e036208f2402182a1af2a59e3c5d7dd44,citation,http://dl.acm.org/citation.cfm?id=3206038,Face Retrieval Framework Relying on User's Visual Memory,2018 +301,LFW,lfw,47.6543238,-122.30800894,University of Washington,edu,09ce14b84af2dc2f76ae1cf227356fa0ba337d07,citation,http://grail.cs.washington.edu/3dfaces/paper.pdf,Face reconstruction in the wild,2011 +302,LFW,lfw,13.0222347,77.56718325,Indian Institute of Science Bangalore,edu,d79365336115661b0e8dbbcd4b2aa1f504b91af6,citation,https://arxiv.org/pdf/1603.01801.pdf,Variational methods for conditional multimodal deep learning,2017 +303,LFW,lfw,31.30104395,121.50045497,Fudan University,edu,7df4f96138a4e23492ea96cf921794fc5287ba72,citation,https://arxiv.org/pdf/1707.08705.pdf,A Jointly Learned Deep Architecture for Facial Attribute Analysis and Face Detection in the Wild,2017 +304,LFW,lfw,22.42031295,114.20788644,Chinese University of Hong Kong,edu,6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4,citation,http://arxiv.org/pdf/1411.7766v2.pdf,Deep Learning Face Attributes in the Wild,2015 +305,LFW,lfw,23.143197,113.34009651,South China Normal University,edu,dc6ad30c7a4bc79bb06b4725b16e202d3d7d8935,citation,http://doi.org/10.1007/s11042-017-4646-5,Age classification with deep learning face representation,2017 +306,LFW,lfw,23.0502042,113.39880323,South China University of Technology,edu,dc6ad30c7a4bc79bb06b4725b16e202d3d7d8935,citation,http://doi.org/10.1007/s11042-017-4646-5,Age classification with deep learning face representation,2017 +307,LFW,lfw,32.0565957,118.77408833,Nanjing University,edu,bbcb4920b312da201bf4d2359383fb4ee3b17ed9,citation,http://pdfs.semanticscholar.org/bbcb/4920b312da201bf4d2359383fb4ee3b17ed9.pdf,Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression,2016 +308,LFW,lfw,32.0575279,118.78682252,Southeast University,edu,feb6e267923868bff6e2108603d00fdfd65251ca,citation,http://pdfs.semanticscholar.org/feb6/e267923868bff6e2108603d00fdfd65251ca.pdf,Unsupervised Discovery of Visual Face Categories,2013 +309,LFW,lfw,24.7246403,46.62335012,King Saud University,edu,feb6e267923868bff6e2108603d00fdfd65251ca,citation,http://pdfs.semanticscholar.org/feb6/e267923868bff6e2108603d00fdfd65251ca.pdf,Unsupervised Discovery of Visual Face Categories,2013 +310,LFW,lfw,39.5469449,-119.81346566,University of Nevada,edu,feb6e267923868bff6e2108603d00fdfd65251ca,citation,http://pdfs.semanticscholar.org/feb6/e267923868bff6e2108603d00fdfd65251ca.pdf,Unsupervised Discovery of Visual Face Categories,2013 +311,LFW,lfw,42.36782045,-71.12666653,Harvard University,edu,8f6263e4d3775757e804796e104631c7a2bb8679,citation,http://pdfs.semanticscholar.org/8f62/63e4d3775757e804796e104631c7a2bb8679.pdf,Characterizing Visual Representations within Convolutional Neural Networks: Toward a Quantitative Approach,2016 +312,LFW,lfw,53.406179,-2.96670819,University of Liverpool,edu,2ab034e1f54c37bfc8ae93f7320160748310dc73,citation,https://arxiv.org/pdf/1805.07242.pdf,Siamese Capsule Networks,2018 +313,LFW,lfw,44.4962318,11.354157,University of Bologna,edu,1d1a7ef193b958f9074f4f236060a5f5e7642fc1,citation,http://pdfs.semanticscholar.org/db40/804914afbb7f8279ca9a4f52e0ade695f19e.pdf,Ensemble of Patterns of Oriented Edge Magnitudes Descriptors For Face Recognition,2013 +314,LFW,lfw,31.20081505,121.42840681,Shanghai Jiao Tong University,edu,36486944b4feeb88c0499fecd253c5a53034a23f,citation,https://doi.org/10.1109/CISP-BMEI.2017.8301986,Deep feature selection and projection for cross-age face retrieval,2017 +315,LFW,lfw,49.443232,1.099971,"IRSEEM Rouen, France",edu,e7436b8e68bb7139b823a7572af3decd96241e78,citation,https://doi.org/10.1109/ROBIO.2011.6181560,A new approach for face detection with omnidirectional sensors,2011 +316,LFW,lfw,49.3849757,1.0683257,"University of Rouen, France",edu,e7436b8e68bb7139b823a7572af3decd96241e78,citation,https://doi.org/10.1109/ROBIO.2011.6181560,A new approach for face detection with omnidirectional sensors,2011 +317,LFW,lfw,48.8476037,2.2639934,"Université Paris-Saclay, France",edu,96e318f8ff91ba0b10348d4de4cb7c2142eb8ba9,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8364450,State-of-the-art face recognition performance using publicly available software and datasets,2018 +318,LFW,lfw,40.00229045,116.32098908,Tsinghua University,edu,e8523c4ac9d7aa21f3eb4062e09f2a3bc1eedcf7,citation,https://arxiv.org/pdf/1701.07174.pdf,Toward End-to-End Face Recognition Through Alignment Learning,2017 +319,LFW,lfw,47.6543238,-122.30800894,University of Washington,edu,405526dfc79de98f5bf3c97bf4aa9a287700f15d,citation,http://pdfs.semanticscholar.org/8a6c/57fcd99a77982ec754e0b97fd67519ccb60c.pdf,MegaFace: A Million Faces for Recognition at Scale,2015 +320,LFW,lfw,42.4505507,-76.4783513,Cornell University,edu,053b263b4a4ccc6f9097ad28ebf39c2957254dfb,citation,http://pdfs.semanticscholar.org/7a49/4b4489408ec3adea15817978ecd2e733f5fe.pdf,Cost-Effective HITs for Relative Similarity Comparisons,2014 +321,LFW,lfw,32.87935255,-117.23110049,"University of California, San Diego",edu,053b263b4a4ccc6f9097ad28ebf39c2957254dfb,citation,http://pdfs.semanticscholar.org/7a49/4b4489408ec3adea15817978ecd2e733f5fe.pdf,Cost-Effective HITs for Relative Similarity Comparisons,2014 +322,LFW,lfw,37.4102193,-122.05965487,Carnegie Mellon 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Telecommunications,edu,cd6aaa37fffd0b5c2320f386be322b8adaa1cc68,citation,https://arxiv.org/pdf/1804.06655.pdf,Deep Face Recognition: A Survey,2018 +368,LFW,lfw,-33.8809651,151.20107299,University of Technology Sydney,edu,e4e3faa47bb567491eaeaebb2213bf0e1db989e1,citation,http://pdfs.semanticscholar.org/e4e3/faa47bb567491eaeaebb2213bf0e1db989e1.pdf,Empirical Risk Minimization for Metric Learning Using Privileged Information,2016 +369,LFW,lfw,31.846918,117.29053367,Hefei University of Technology,edu,e4e3faa47bb567491eaeaebb2213bf0e1db989e1,citation,http://pdfs.semanticscholar.org/e4e3/faa47bb567491eaeaebb2213bf0e1db989e1.pdf,Empirical Risk Minimization for Metric Learning Using Privileged Information,2016 +370,LFW,lfw,23.1353836,113.29470496,Guangdong University of Technology,edu,4b02387c2db968a70b69d98da3c443f139099e91,citation,http://pdfs.semanticscholar.org/4b02/387c2db968a70b69d98da3c443f139099e91.pdf,Detecting facial landmarks in the video based on a hybrid framework,2016 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Technology,edu,8ee5b1c9fb0bded3578113c738060290403ed472,citation,https://infoscience.epfl.ch/record/200452/files/wacv2014-RGE.pdf,Extending explicit shape regression with mixed feature channels and pose priors,2014 +375,LFW,lfw,49.2579566,7.04577417,Max Planck Institute for Informatics,edu,0c59071ddd33849bd431165bc2d21bbe165a81e0,citation,http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Oh_Person_Recognition_in_ICCV_2015_paper.pdf,Person Recognition in Personal Photo Collections,2015 +376,LFW,lfw,36.20304395,117.05842113,Tianjin University,edu,4223917177405eaa6bdedca061eb28f7b440ed8e,citation,http://pdfs.semanticscholar.org/4223/917177405eaa6bdedca061eb28f7b440ed8e.pdf,B-spline Shape from Motion & Shading: An Automatic Free-form Surface Modeling for Face Reconstruction,2016 +377,LFW,lfw,2.92749755,101.64185301,Multimedia 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University of Singapore,edu,c17c7b201cfd0bcd75441afeaa734544c6ca3416,citation,https://doi.org/10.1109/TCSVT.2016.2587389,Layerwise Class-Aware Convolutional Neural Network,2017 +431,LFW,lfw,32.0575279,118.78682252,Southeast University,edu,c17c7b201cfd0bcd75441afeaa734544c6ca3416,citation,https://doi.org/10.1109/TCSVT.2016.2587389,Layerwise Class-Aware Convolutional Neural Network,2017 +432,LFW,lfw,29.7207902,-95.34406271,University of Houston,edu,e6da1fcd2a8cda0c69b3d94812caa7d844903007,citation,http://dl.acm.org/citation.cfm?id=3137154,"Sonicdoor: scaling person identification with ultrasonic sensors by novel modeling of shape, behavior and walking patterns",2017 +433,LFW,lfw,23.09461185,113.28788994,Sun Yat-Sen University,edu,cd74d606e76ecddee75279679d9770cdc0b49861,citation,https://doi.org/10.1109/TIP.2014.2365725,Transfer Learning of Structured Representation for Face Recognition,2014 +434,LFW,lfw,23.7289899,90.3982682,Institute of Information 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radial gradient transform based face recognition,2015 +465,LFW,lfw,42.3583961,-71.09567788,MIT,edu,5e0e516226413ea1e973f1a24e2fdedde98e7ec0,citation,http://pdfs.semanticscholar.org/74ce/97da57ec848db660ee69dec709f226c74f43.pdf,The Invariance Hypothesis and the Ventral Stream,2013 +466,LFW,lfw,53.21967825,6.56251482,University of Groningen,edu,d8896861126b7fd5d2ceb6fed8505a6dff83414f,citation,http://pdfs.semanticscholar.org/d889/6861126b7fd5d2ceb6fed8505a6dff83414f.pdf,In-plane Rotational Alignment of Faces by Eye and Eye-pair Detection,2015 +467,LFW,lfw,39.9808333,116.34101249,Beihang University,edu,70d2ab1af0edd5c0a30d576a5d4aa397c4f92d3e,citation,http://doi.org/10.1007/s11042-018-5608-2,Elastic preserving projections based on L1-norm maximization,2018 +468,LFW,lfw,38.99203005,-76.9461029,University of Maryland College Park,edu,b2cd92d930ed9b8d3f9dfcfff733f8384aa93de8,citation,http://pdfs.semanticscholar.org/b2cd/92d930ed9b8d3f9dfcfff733f8384aa93de8.pdf,"HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition",2016 +469,LFW,lfw,39.2899685,-76.62196103,University of Maryland,edu,b2cd92d930ed9b8d3f9dfcfff733f8384aa93de8,citation,http://pdfs.semanticscholar.org/b2cd/92d930ed9b8d3f9dfcfff733f8384aa93de8.pdf,"HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition",2016 +470,LFW,lfw,35.9042272,-78.85565763,"IBM Research, North Carolina",company,148eb413bede35487198ce7851997bf8721ea2d6,citation,http://pdfs.semanticscholar.org/148e/b413bede35487198ce7851997bf8721ea2d6.pdf,People Search in Surveillance Videos,2009 +471,LFW,lfw,38.8964679,-104.8050594,University of Colorado at Colorado Springs,edu,e3e2c106ccbd668fb9fca851498c662add257036,citation,http://www.vast.uccs.edu/~tboult/PAPERS/BTAS13-Sapkota-et-al-Ensembles.pdf,"Appearance, context and co-occurrence ensembles for identity recognition in personal photo collections",2013 +472,LFW,lfw,42.3383668,-71.08793524,Northeastern University,edu,d22b378fb4ef241d8d210202893518d08e0bb213,citation,http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Zhang_Random_Faces_Guided_2013_ICCV_paper.pdf,Random Faces Guided Sparse Many-to-One Encoder for Pose-Invariant Face Recognition,2013 +473,LFW,lfw,1.2962018,103.77689944,National University of Singapore,edu,dbb9601a1d2febcce4c07dd2b819243d81abb2c2,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8361884,Landmark Free Face Attribute Prediction,2018 +474,LFW,lfw,1.27486,103.797787,"SAP Innovation Center Network, Singapore",company,dbb9601a1d2febcce4c07dd2b819243d81abb2c2,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8361884,Landmark Free Face Attribute Prediction,2018 +475,LFW,lfw,37.4092265,-122.0236615,"Baidu Research, USA",company,8633732d9f787f8497c2696309c7d70176995c15,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7298967,Multi-objective convolutional learning for face labeling,2015 +476,LFW,lfw,37.36566745,-120.42158888,"University of California, Merced",edu,8633732d9f787f8497c2696309c7d70176995c15,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7298967,Multi-objective convolutional learning for face labeling,2015 +477,LFW,lfw,42.718568,-84.47791571,Michigan State University,edu,7fb5006b6522436ece5bedf509e79bdb7b79c9a7,citation,https://pdfs.semanticscholar.org/7fb5/006b6522436ece5bedf509e79bdb7b79c9a7.pdf,Multi-Task Convolutional Neural Network for Face Recognition,2017 +478,LFW,lfw,42.3889785,-72.5286987,University of Massachusetts,edu,368e99f669ea5fd395b3193cd75b301a76150f9d,citation,https://arxiv.org/pdf/1506.01342.pdf,One-to-many face recognition with bilinear CNNs,2016 +479,LFW,lfw,33.5866784,-101.87539204,Electrical and Computer 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Florida,edu,c07ab025d9e3c885ad5386e6f000543efe091c4b,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8302601,Preserving Model Privacy for Machine Learning in Distributed Systems,2018 +487,LFW,lfw,39.9922379,116.30393816,Peking University,edu,5798055e11e25c404b1b0027bc9331bcc6e00555,citation,http://doi.acm.org/10.1145/2393347.2396357,PDSS: patch-descriptor-similarity space for effective face verification,2012 +488,LFW,lfw,51.49887085,-0.17560797,Imperial College London,edu,c43ed9b34cad1a3976bac7979808eb038d88af84,citation,https://arxiv.org/pdf/1804.03675.pdf,Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,2018 +489,LFW,lfw,51.24303255,-0.59001382,University of Surrey,edu,c43ed9b34cad1a3976bac7979808eb038d88af84,citation,https://arxiv.org/pdf/1804.03675.pdf,Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,2018 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manifold constrained joint sparse sensing with K-SVD,2018 +498,LFW,lfw,31.2284923,121.40211389,East China Normal University,edu,06518858bd99cddf9bc9200fac5311fc29ac33b4,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8392777,Sparse Low-Rank Component-Based Representation for Face Recognition With Low-Quality Images,2019 +499,LFW,lfw,31.28473925,121.49694909,Tongji University,edu,06518858bd99cddf9bc9200fac5311fc29ac33b4,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8392777,Sparse Low-Rank Component-Based Representation for Face Recognition With Low-Quality Images,2019 +500,LFW,lfw,39.87391435,116.47722285,Beijing University of Technology,edu,f1d6da83dcf71eda45a56a86c5ae13e7f45a8536,citation,https://doi.org/10.1109/ACCESS.2017.2737544,A Secure Face-Verification Scheme Based on Homomorphic Encryption and Deep Neural Networks,2017 +501,LFW,lfw,25.0410728,121.6147562,Institute of Information Science,edu,337dd4aaca2c5f9b5d2de8e0e2401b5a8feb9958,citation,https://arxiv.org/pdf/1810.11160.pdf,Data-specific Adaptive Threshold for Face Recognition and Authentication,2018 +502,LFW,lfw,37.4102193,-122.05965487,Carnegie Mellon University,edu,4d16337cc0431cd43043dfef839ce5f0717c3483,citation,http://pdfs.semanticscholar.org/4d16/337cc0431cd43043dfef839ce5f0717c3483.pdf,A Scalable and Privacy-Aware IoT Service for Live Video Analytics,2017 +503,LFW,lfw,22.59805605,113.98533784,Shenzhen Institutes of Advanced Technology,edu,1d696a1beb42515ab16f3a9f6f72584a41492a03,citation,http://www.ee.cuhk.edu.hk/~xgwang/papers/sunWTcvpr15.pdf,"Deeply learned face representations are sparse, selective, and robust",2015 +504,LFW,lfw,22.42031295,114.20788644,Chinese University of Hong Kong,edu,1d696a1beb42515ab16f3a9f6f72584a41492a03,citation,http://www.ee.cuhk.edu.hk/~xgwang/papers/sunWTcvpr15.pdf,"Deeply learned face representations are sparse, selective, and robust",2015 +505,LFW,lfw,53.8925662,-122.81471592,University of Northern British Columbia,edu,683ec608442617d11200cfbcd816e86ce9ec0899,citation,http://doi.ieeecomputersociety.org/10.1109/CVPR.2014.342,Dual Linear Regression Based Classification for Face Cluster Recognition,2014 +506,LFW,lfw,45.42580475,-75.68740118,University of Ottawa,edu,65293ecf6a4c5ab037a2afb4a9a1def95e194e5f,citation,http://pdfs.semanticscholar.org/6529/3ecf6a4c5ab037a2afb4a9a1def95e194e5f.pdf,"Face , Age and Gender Recognition using Local Descriptors",2014 +507,LFW,lfw,28.54632595,77.27325504,Indian Institute of Technology Delhi,edu,25d514d26ecbc147becf4117512523412e1f060b,citation,https://doi.org/10.1109/ICB.2015.7139083,Annotated crowd video face database,2015 +508,LFW,lfw,40.62984145,22.9588935,Aristotle University of Thessaloniki,edu,e40cb4369c6402ae53c81ce52b73df3ef89f578b,citation,http://doi.org/10.1016/j.image.2015.01.009,Facial image clustering in stereoscopic videos using double spectral analysis,2015 +509,LFW,lfw,42.3889785,-72.5286987,University of Massachusetts,edu,2d3482dcff69c7417c7b933f22de606a0e8e42d4,citation,http://pdfs.semanticscholar.org/2d34/82dcff69c7417c7b933f22de606a0e8e42d4.pdf,Labeled Faces in the Wild : Updates and New Reporting Procedures,2014 +510,LFW,lfw,40.00229045,116.32098908,Tsinghua University,edu,4ea4116f57c5d5033569690871ba294dc3649ea5,citation,http://pdfs.semanticscholar.org/4ea4/116f57c5d5033569690871ba294dc3649ea5.pdf,Multi-View Face Alignment Using 3D Shape Model for View Estimation,2009 +511,LFW,lfw,51.49887085,-0.17560797,Imperial College London,edu,7cffcb4f24343a924a8317d560202ba9ed26cd0b,citation,https://arxiv.org/pdf/1708.06997.pdf,The unconstrained ear recognition challenge,2017 +512,LFW,lfw,34.8452999,48.5596212,Islamic Azad University,edu,7cffcb4f24343a924a8317d560202ba9ed26cd0b,citation,https://arxiv.org/pdf/1708.06997.pdf,The unconstrained ear recognition challenge,2017 +513,LFW,lfw,38.8920756,-104.79716389,"University of Colorado, Colorado Springs",edu,7cffcb4f24343a924a8317d560202ba9ed26cd0b,citation,https://arxiv.org/pdf/1708.06997.pdf,The unconstrained ear recognition challenge,2017 +514,LFW,lfw,46.0501558,14.46907327,University of Ljubljana,edu,7cffcb4f24343a924a8317d560202ba9ed26cd0b,citation,https://arxiv.org/pdf/1708.06997.pdf,The unconstrained ear recognition challenge,2017 +515,LFW,lfw,17.4454957,78.34854698,International Institute of Information Technology,edu,185263189a30986e31566394680d6d16b0089772,citation,https://pdfs.semanticscholar.org/1852/63189a30986e31566394680d6d16b0089772.pdf,Efficient Annotation of Objects for Video Analysis,2018 +516,LFW,lfw,42.718568,-84.47791571,Michigan State University,edu,5da827fe558fb2e1124dcc84ef08311241761726,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7139096,Attribute preserved face de-identification,2015 +517,LFW,lfw,24.4399419,118.09301781,Xiamen University,edu,1de23d7fe718d9fab0159f58f422099e44ad3f0a,citation,http://doi.org/10.1007/s11063-016-9558-2,Locality Preserving Collaborative Representation for Face Recognition,2016 +518,LFW,lfw,39.2899685,-76.62196103,University of Maryland,edu,4f7b92bd678772552b3c3edfc9a7c5c4a8c60a8e,citation,https://pdfs.semanticscholar.org/4f7b/92bd678772552b3c3edfc9a7c5c4a8c60a8e.pdf,Deep Density Clustering of Unconstrained Faces,0 +519,LFW,lfw,35.97320905,-78.89755054,North Carolina Central University,edu,5bb53fb36a47b355e9a6962257dd465cd7ad6827,citation,http://pdfs.semanticscholar.org/5bb5/3fb36a47b355e9a6962257dd465cd7ad6827.pdf,Mask-off: Synthesizing Face Images in the Presence of Head-mounted Displays,2016 +520,LFW,lfw,38.0333742,-84.5017758,University of Kentucky,edu,5bb53fb36a47b355e9a6962257dd465cd7ad6827,citation,http://pdfs.semanticscholar.org/5bb5/3fb36a47b355e9a6962257dd465cd7ad6827.pdf,Mask-off: Synthesizing Face Images in the Presence of Head-mounted Displays,2016 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Appearance and Shape for AAM Ensemble Fitting,2013 +533,LFW,lfw,40.34829285,-74.66308325,Princeton University,edu,818ecc8c8d4dc398b01a852df90cb8d972530fa5,citation,https://arxiv.org/pdf/1806.06098.pdf,Unsupervised Training for 3D Morphable Model Regression,2018 +534,LFW,lfw,42.3619407,-71.0904378,MIT CSAIL,edu,818ecc8c8d4dc398b01a852df90cb8d972530fa5,citation,https://arxiv.org/pdf/1806.06098.pdf,Unsupervised Training for 3D Morphable Model Regression,2018 +535,LFW,lfw,31.83907195,117.26420748,University of Science and Technology of China,edu,d99b5ee3e2d7e3a016fbc5fd417304e15efbd1f8,citation,http://doi.org/10.1007/s11063-017-9578-6,A Novel Two-stage Learning Pipeline for Deep Neural Networks,2017 +536,LFW,lfw,38.8920756,-104.79716389,"University of Colorado, Colorado Springs",edu,4b3f425274b0c2297d136f8833a31866db2f2aec,citation,http://doi.ieeecomputersociety.org/10.1109/CVPRW.2017.85,Toward Open-Set Face Recognition,2017 +537,LFW,lfw,46.0501558,14.46907327,University of Ljubljana,edu,12003a7d65c4f98fb57587fd0e764b44d0d10125,citation,http://doi.ieeecomputersociety.org/10.1109/FG.2015.7284835,Face recognition in the wild with the Probabilistic Gabor-Fisher Classifier,2015 +538,LFW,lfw,36.3697191,127.362537,Korea Advanced Institute of Science and Technology,edu,7a09e8f65bd85d4c79f0ae90d4e2685869a9894f,citation,https://doi.org/10.1109/TMM.2016.2551698,Face and Hair Region Labeling Using Semi-Supervised Spectral Clustering-Based Multiple Segmentations,2016 +539,LFW,lfw,36.399184,127.394656,Korea Institute of Oriental Medicine,edu,7a09e8f65bd85d4c79f0ae90d4e2685869a9894f,citation,https://doi.org/10.1109/TMM.2016.2551698,Face and Hair Region Labeling Using Semi-Supervised Spectral Clustering-Based Multiple Segmentations,2016 +540,LFW,lfw,41.21002475,-73.80407056,IBM Thomas J. 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Information Science,edu,0106a2f6251dc9ffc90709c6f0d9b54c1e82326b,citation,http://www.iis.sinica.edu.tw/papers/song/14922-A.pdf,Applying scattering operators for face recognition: A comparative study,2012 +640,LFW,lfw,25.01682835,121.53846924,National Taiwan University,edu,0106a2f6251dc9ffc90709c6f0d9b54c1e82326b,citation,http://www.iis.sinica.edu.tw/papers/song/14922-A.pdf,Applying scattering operators for face recognition: A comparative study,2012 +641,LFW,lfw,35.0274996,135.78154513,University of Caen,edu,0ad8149318912b5449085187eb3521786a37bc78,citation,http://arxiv.org/abs/1604.02975,CP-mtML: Coupled Projection Multi-Task Metric Learning for Large Scale Face Retrieval,2016 +642,LFW,lfw,49.2579566,7.04577417,Max Planck Institute for Informatics,edu,bc27434e376db89fe0e6ef2d2fabc100d2575ec6,citation,https://arxiv.org/pdf/1607.08438.pdf,Faceless Person Recognition; Privacy Implications in Social Media,2016 +643,LFW,lfw,31.2284923,121.40211389,East China Normal 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face and pose recovery,2010 +682,LFW,lfw,1.3484104,103.68297965,Nanyang Technological University,edu,28be652db01273289499bc6e56379ca0237506c0,citation,http://www.cv-foundation.org/openaccess/content_cvpr_2015/app/3B_018_ext.pdf,FaLRR: A fast low rank representation solver,2015 +683,LFW,lfw,50.8142701,8.771435,Philipps-Universität Marburg,edu,5981c309bd0ffd849c51b1d8a2ccc481a8ec2f5c,citation,https://doi.org/10.1109/ICT.2017.7998256,SmartFace: Efficient face detection on smartphones for wireless on-demand emergency networks,2017 +684,LFW,lfw,40.0044795,116.370238,Chinese Academy of Sciences,edu,1a40c2a2d17c52c8b9d20648647d0886e30a60fa,citation,https://doi.org/10.1109/ICPR.2016.7900283,Hybrid hypergraph construction for facial expression recognition,2016 +685,LFW,lfw,24.8186587,67.0316585,Shaheed Zulfikar Ali Bhutto Institute of Science and Technology,edu,70580ed8bc482cad66e059e838e4a779081d1648,citation,http://pdfs.semanticscholar.org/7058/0ed8bc482cad66e059e838e4a779081d1648.pdf,Gender Classification using Multi-Level Wavelets on Real World Face Images,2013 +686,LFW,lfw,37.4102193,-122.05965487,Carnegie Mellon University,edu,9fc04a13eef99851136eadff52e98eb9caac919d,citation,http://pdfs.semanticscholar.org/9fc0/4a13eef99851136eadff52e98eb9caac919d.pdf,Rethinking the Camera Pipeline for Computer Vision,2017 +687,LFW,lfw,42.4505507,-76.4783513,Cornell University,edu,9fc04a13eef99851136eadff52e98eb9caac919d,citation,http://pdfs.semanticscholar.org/9fc0/4a13eef99851136eadff52e98eb9caac919d.pdf,Rethinking the Camera Pipeline for Computer Vision,2017 +688,LFW,lfw,40.51865195,-74.44099801,State University of New Jersey,edu,0ca66283f4fb7dbc682f789fcf6d6732006befd5,citation,http://pdfs.semanticscholar.org/0ca6/6283f4fb7dbc682f789fcf6d6732006befd5.pdf,Active Dictionary Learning for Image Representation,2015 +689,LFW,lfw,65.0592157,25.46632601,University of Oulu,edu,761304bbd259a9e419a2518193e1ff1face9fd2d,citation,https://doi.org/10.1007/978-3-642-33885-4_57,Robust and Computationally Efficient Face Detection Using Gaussian Derivative Features of Higher Orders,2012 +690,LFW,lfw,13.0222347,77.56718325,Indian Institute of Science Bangalore,edu,f5af3c28b290dc797c499283e2d0662570f9ed02,citation,https://pdfs.semanticscholar.org/f5af/3c28b290dc797c499283e2d0662570f9ed02.pdf,GenLR-Net : Deep framework for very low resolution face and object recognition with generalization to unseen categories,2018 +691,LFW,lfw,22.42031295,114.20788644,Chinese University of Hong Kong,edu,a0d6390dd28d802152f207940c7716fe5fae8760,citation,http://pdfs.semanticscholar.org/a0d6/390dd28d802152f207940c7716fe5fae8760.pdf,Bayesian Face Revisited: A Joint Formulation,2012 +692,LFW,lfw,31.83907195,117.26420748,University of Science and Technology of China,edu,a0d6390dd28d802152f207940c7716fe5fae8760,citation,http://pdfs.semanticscholar.org/a0d6/390dd28d802152f207940c7716fe5fae8760.pdf,Bayesian Face Revisited: A Joint Formulation,2012 +693,LFW,lfw,45.7833244,4.8781984,University of Lyon,edu,54ba18952fe36c9be9f2ab11faecd43d123b389b,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7163085,Triangular similarity metric learning for face verification,2015 +694,LFW,lfw,-27.5953995,-48.6154218,University of Campinas,edu,a2bd81be79edfa8dcfde79173b0a895682d62329,citation,http://pdfs.semanticscholar.org/a2bd/81be79edfa8dcfde79173b0a895682d62329.pdf,Multi-Objective Vehicle Routing Problem Applied to Large Scale Post Office Deliveries,2017 +695,LFW,lfw,22.59805605,113.98533784,Shenzhen Institutes of Advanced Technology,edu,4cfd770ccecae1c0b4248bc800d7fd35c817bbbd,citation,https://pdfs.semanticscholar.org/8774/e206564df3bf9050f8c2be6b434cc2469c5b.pdf,A Discriminative Feature Learning Approach for Deep Face Recognition,2016 +696,LFW,lfw,22.42031295,114.20788644,Chinese University of Hong Kong,edu,4cfd770ccecae1c0b4248bc800d7fd35c817bbbd,citation,https://pdfs.semanticscholar.org/8774/e206564df3bf9050f8c2be6b434cc2469c5b.pdf,A Discriminative Feature Learning Approach for Deep Face Recognition,2016 +697,LFW,lfw,43.08250655,-77.67121663,Rochester Institute of Technology,edu,69b2a7533e38c2c8c9a0891a728abb423ad2c7e7,citation,https://doi.org/10.1016/j.imavis.2013.03.003,Manifold based sparse representation for facial understanding in natural images,2013 +698,LFW,lfw,49.2579566,7.04577417,Max Planck Institute for Informatics,edu,0df0d1adea39a5bef318b74faa37de7f3e00b452,citation,https://scalable.mpi-inf.mpg.de/files/2015/09/zhang_CVPR15.pdf,Appearance-based gaze estimation in the wild,2015 +699,LFW,lfw,59.34986645,18.07063213,"KTH Royal Institute of Technology, Stockholm",edu,633101e794d7b80f55f466fd2941ea24595e10e6,citation,https://pdfs.semanticscholar.org/6331/01e794d7b80f55f466fd2941ea24595e10e6.pdf,Face Attribute Prediction with classification CNN,2016 +700,LFW,lfw,39.1254938,-77.22293475,National Institute of Standards and Technology,edu,089b5e8eb549723020b908e8eb19479ba39812f5,citation,http://www.face-recognition-challenge.com/RobustnessOfDCNN-preprint.pdf,A Cross Benchmark Assessment of a Deep Convolutional Neural Network for Face Recognition,2017 +701,LFW,lfw,-27.49741805,153.01316956,University of Queensland,edu,f27fd2a1bc229c773238f1912db94991b8bf389a,citation,https://doi.org/10.1109/IVCNZ.2016.7804414,How do you develop a face detector for the unconstrained environment?,2016 +702,LFW,lfw,40.47913175,-74.43168868,Rutgers University,edu,afdf9a3464c3b015f040982750f6b41c048706f5,citation,https://arxiv.org/pdf/1608.05477.pdf,A Recurrent Encoder-Decoder Network for Sequential Face Alignment,2016 +703,LFW,lfw,40.00229045,116.32098908,Tsinghua University,edu,a52a69bf304d49fba6eac6a73c5169834c77042d,citation,https://doi.org/10.1109/LSP.2017.2789251,Margin Loss: Making Faces More Separable,2018 +704,LFW,lfw,40.0044795,116.370238,Chinese Academy of Sciences,edu,bc910ca355277359130da841a589a36446616262,citation,http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Huang_Conditional_High-Order_Boltzmann_ICCV_2015_paper.pdf,Conditional High-Order Boltzmann Machine: A Supervised Learning Model for Relation Learning,2015 +705,LFW,lfw,40.00229045,116.32098908,Tsinghua University,edu,93eb3963bc20e28af26c53ef3bce1e76b15e3209,citation,https://doi.org/10.1109/ICIP.2017.8296992,Occlusion robust face recognition based on mask learning,2017 +706,LFW,lfw,51.49887085,-0.17560797,Imperial College London,edu,a06b6d30e2b31dc600f622ab15afe5e2929581a7,citation,https://ibug.doc.ic.ac.uk/media/uploads/documents/2209.pdf,Robust Joint and Individual Variance Explained,2017 +707,LFW,lfw,51.59029705,-0.22963221,Middlesex University,edu,a06b6d30e2b31dc600f622ab15afe5e2929581a7,citation,https://ibug.doc.ic.ac.uk/media/uploads/documents/2209.pdf,Robust Joint and Individual Variance Explained,2017 +708,LFW,lfw,39.9601488,116.35193921,Beijing University of Posts and Telecommunications,edu,565f7c767e6b150ebda491e04e6b1de759fda2d4,citation,https://doi.org/10.1016/j.patcog.2016.11.023,"Fine-grained face verification: FGLFW database, baselines, and human-DCMN partnership",2017 +709,LFW,lfw,40.0141905,-83.0309143,University of Electronic Science and Technology of China,edu,16b9d258547f1eccdb32111c9f45e2e4bbee79af,citation,https://arxiv.org/pdf/1704.06369.pdf,NormFace: L2 Hypersphere Embedding for Face Verification,2017 +710,LFW,lfw,40.0044795,116.370238,Chinese Academy of Sciences,edu,a73405038fdc0d8bf986539ef755a80ebd341e97,citation,https://doi.org/10.1109/TIP.2017.2698918,Conditional High-Order Boltzmann Machines for Supervised Relation Learning,2017 +711,LFW,lfw,-32.00686365,115.89691775,Curtin University,edu,e9a5a38e7da3f0aa5d21499149536199f2e0e1f7,citation,https://pdfs.semanticscholar.org/e9a5/a38e7da3f0aa5d21499149536199f2e0e1f7.pdf,A Bayesian Scene-Prior-Based Deep Network Model for Face Verification,2018 +712,LFW,lfw,65.0592157,25.46632601,University of Oulu,edu,1fe121925668743762ce9f6e157081e087171f4c,citation,https://www.cv-foundation.org/openaccess/content_cvpr_workshops_2015/W02/papers/Ylioinas_Unsupervised_Learning_of_2015_CVPR_paper.pdf,Unsupervised learning of overcomplete face descriptors,2015 +713,LFW,lfw,-35.23656905,149.08446994,University of Canberra,edu,6f2b36cadf3dd1648b709e9b4f4c19ffa1939ed1,citation,https://arxiv.org/pdf/1901.07590.pdf,Striking the Right Balance with Uncertainty,2019 +714,LFW,lfw,-35.2776999,149.118527,Australian National University,edu,84c7d3b1d407e0d435a08574a3f82ecacf7841b6,citation,https://arxiv.org/pdf/1901.07711.pdf,Max-margin Class Imbalanced Learning with Gaussian Affinity,2019 +715,LFW,lfw,39.9601488,116.35193921,Beijing University of Posts and Telecommunications,edu,0be418e63d111e3b94813875f75909e4dc27d13a,citation,https://doi.org/10.1109/ICB.2016.7550057,Fine-grained LFW database,2016 +716,LFW,lfw,-27.49741805,153.01316956,University of Queensland,edu,3c563542db664321aa77a9567c1601f425500f94,citation,https://arxiv.org/pdf/1712.02514.pdf,TV-GAN: Generative Adversarial Network Based Thermal to Visible Face Recognition,2018 +717,LFW,lfw,36.20304395,117.05842113,Tianjin University,edu,1bf570bd40b3adced1e47dbcceffe50573f81845,citation,https://arxiv.org/pdf/1803.02504.pdf,Exponential Discriminative Metric Embedding in Deep Learning,2018 +718,LFW,lfw,25.01682835,121.53846924,National Taiwan University,edu,81884e1de00e59f24bc20254584d73a1a1806933,citation,https://arxiv.org/pdf/1811.02328.pdf,Super-Identity Convolutional Neural Network for Face Hallucination,2018 +719,LFW,lfw,39.993008,116.329882,SenseTime,company,81884e1de00e59f24bc20254584d73a1a1806933,citation,https://arxiv.org/pdf/1811.02328.pdf,Super-Identity Convolutional Neural Network for Face Hallucination,2018 +720,LFW,lfw,30.284151,-97.73195598,University of Texas at Austin,edu,81884e1de00e59f24bc20254584d73a1a1806933,citation,https://arxiv.org/pdf/1811.02328.pdf,Super-Identity Convolutional Neural Network for Face Hallucination,2018 +721,LFW,lfw,32.77824165,34.99565673,Open University of Israel,edu,1e6ed6ca8209340573a5e907a6e2e546a3bf2d28,citation,http://arxiv.org/pdf/1607.01450v1.pdf,Pooling Faces: Template Based Face Recognition with Pooled Face Images,2016 +722,LFW,lfw,37.5600406,126.9369248,Yonsei University,edu,06c956d4aac65752672ce4bd5a379f10a7fd6148,citation,https://doi.org/10.1109/LSP.2017.2749763,Stacking PCANet +: An Overly Simplified ConvNets Baseline for Face Recognition,2017 +723,LFW,lfw,52.2380139,6.8566761,University of Twente,edu,740e095a65524d569244947f6eea3aefa3cca526,citation,http://pdfs.semanticscholar.org/740e/095a65524d569244947f6eea3aefa3cca526.pdf,Towards Human-like Performance Face Detection: A Convolutional Neural Network Approach,2016 +724,LFW,lfw,32.1119889,34.80459702,Tel Aviv University,edu,2f16baddac6af536451b3216b02d3480fc361ef4,citation,http://cs.nyu.edu/~fergus/teaching/vision/10_facerec.pdf,Web-scale training for face identification,2015 +725,LFW,lfw,42.4505507,-76.4783513,Cornell University,edu,32d8e555441c47fc27249940991f80502cb70bd5,citation,https://arxiv.org/pdf/1709.07886v1.pdf,Machine Learning Models that Remember Too Much,2017 +726,LFW,lfw,32.1119889,34.80459702,Tel Aviv University,edu,7859667ed6c05a467dfc8a322ecd0f5e2337db56,citation,http://pdfs.semanticscholar.org/7859/667ed6c05a467dfc8a322ecd0f5e2337db56.pdf,Web-Scale Transfer Learning for Unconstrained 1:N Face Identification,2015 +727,LFW,lfw,29.58333105,-98.61944505,University of Texas at San Antonio,edu,7788fa76f1488b1597ee2bebc462f628e659f61e,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8063888,A Privacy-Aware Architecture at the Edge for Autonomous Real-Time Identity Reidentification in Crowds,2018 +728,LFW,lfw,40.8419836,-73.94368971,Columbia University,edu,f467eb5e7f9d49ab318401f961109882c00f2720,citation,http://www.nsl.cs.columbia.edu/papers/2015/faceoff.ccs15.pdf,Face/Off: Preventing Privacy Leakage From Photos in Social Networks,2015 +729,LFW,lfw,40.2773077,-7.5095801,University of Beira Interior,edu,84ae55603bffda40c225fe93029d39f04793e01f,citation,https://doi.org/10.1109/ICB.2016.7550066,ICB-RW 2016: International challenge on biometric recognition in the wild,2016 +730,LFW,lfw,-33.8809651,151.20107299,University of Technology Sydney,edu,3b64efa817fd609d525c7244a0e00f98feacc8b4,citation,http://doi.acm.org/10.1145/2845089,A Comprehensive Survey on Pose-Invariant Face Recognition,2016 +731,LFW,lfw,32.0575279,118.78682252,Southeast University,edu,b2e308649c7a502456a8e3c95ac7fbe6f8216e51,citation,http://pdfs.semanticscholar.org/b2e3/08649c7a502456a8e3c95ac7fbe6f8216e51.pdf,Recurrent Regression for Face Recognition,2016 +732,LFW,lfw,3.12267405,101.65356103,University of Malaya,edu,5e48958c1c9ab9ccb5c9e1a62b81532700d38d83,citation,https://arxiv.org/pdf/1702.03410.pdf,ArtGAN: Artwork synthesis with conditional categorical GANs,2017 +733,LFW,lfw,39.47787665,-0.34257711,Universitat de València,edu,5922e26c9eaaee92d1d70eae36275bb226ecdb2e,citation,http://pdfs.semanticscholar.org/5922/e26c9eaaee92d1d70eae36275bb226ecdb2e.pdf,Boosting Classification Based Similarity Learning by using Standard Distances,2015 +734,LFW,lfw,42.4505507,-76.4783513,Cornell University,edu,345cc31c85e19cea9f8b8521be6a37937efd41c2,citation,https://arxiv.org/pdf/1511.06421.pdf,Deep Manifold Traversal: Changing Labels with Convolutional Features,2015 +735,LFW,lfw,40.0044795,116.370238,Chinese Academy of Sciences,edu,72a7eb68f0955564e1ceafa75aeeb6b5bbb14e7e,citation,https://pdfs.semanticscholar.org/72a7/eb68f0955564e1ceafa75aeeb6b5bbb14e7e.pdf,Face Recognition with Contrastive Convolution,2018 +736,LFW,lfw,39.9082804,116.2458527,University of Chinese Academy of Sciences,edu,72a7eb68f0955564e1ceafa75aeeb6b5bbb14e7e,citation,https://pdfs.semanticscholar.org/72a7/eb68f0955564e1ceafa75aeeb6b5bbb14e7e.pdf,Face Recognition with Contrastive Convolution,2018 +737,LFW,lfw,31.83907195,117.26420748,University of Science and Technology of China,edu,47cd161546c59ab1e05f8841b82e985f72e5ddcb,citation,https://doi.org/10.1109/ICIP.2017.8296552,Gender classification in live videos,2017 +738,LFW,lfw,37.4102193,-122.05965487,Carnegie Mellon University,edu,bd8f77b7d3b9d272f7a68defc1412f73e5ac3135,citation,https://arxiv.org/pdf/1704.08063.pdf,SphereFace: Deep Hypersphere Embedding for Face Recognition,2017 +739,LFW,lfw,33.776033,-84.39884086,Georgia Institute of Technology,edu,bd8f77b7d3b9d272f7a68defc1412f73e5ac3135,citation,https://arxiv.org/pdf/1704.08063.pdf,SphereFace: Deep Hypersphere Embedding for Face Recognition,2017 +740,LFW,lfw,23.09461185,113.28788994,Sun Yat-Sen University,edu,bd8f77b7d3b9d272f7a68defc1412f73e5ac3135,citation,https://arxiv.org/pdf/1704.08063.pdf,SphereFace: Deep Hypersphere Embedding for Face Recognition,2017 +741,LFW,lfw,42.2942142,-83.71003894,University of Michigan,edu,9ace71283834d4dd72509db6f1b859536f801d1c,citation,https://arxiv.org/pdf/1701.00299.pdf,Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-Offs by Selective Execution,2018 +742,LFW,lfw,22.2081469,114.25964115,University of Hong Kong,edu,e1630014a5ae3d2fb7ff6618f1470a567f4d90f5,citation,https://arxiv.org/pdf/1602.04364.pdf,"Look, Listen and Learn - A Multimodal LSTM for Speaker Identification",2016 +743,LFW,lfw,24.18005755,120.64836072,Feng Chia University,edu,344a5802999dddd0a6d1c4d511910af2eb922231,citation,http://pdfs.semanticscholar.org/f0ba/552418698d1b881c6f9f02e2c84f969e66f3.pdf,DroneFace: An Open Dataset for Drone Research,2017 +744,LFW,lfw,40.0044795,116.370238,Chinese Academy of Sciences,edu,600f164c81dbaa0327e7bd659fd9eb7f511f9e9a,citation,https://doi.org/10.1109/BTAS.2014.6996301,A benchmark study of large-scale unconstrained face recognition,2014 +745,LFW,lfw,36.20304395,117.05842113,Tianjin University,edu,5180df9d5eb26283fb737f491623395304d57497,citation,https://arxiv.org/pdf/1804.10899.pdf,Scalable Angular Discriminative Deep Metric Learning for Face Recognition,2018 +746,LFW,lfw,32.0565957,118.77408833,Nanjing University,edu,55089f9bc858ae7e9addf30502ac11be4347c05a,citation,https://pdfs.semanticscholar.org/5508/9f9bc858ae7e9addf30502ac11be4347c05a.pdf,A Privacy-Preserving Deep Learning Approach for Face Recognition with Edge Computing,2018 +747,LFW,lfw,39.9082804,116.2458527,University of Chinese Academy of Sciences,edu,37af037923d0d7a4480a9c1f2e7d002f122bfebb,citation,https://arxiv.org/pdf/1706.04717.pdf,Recent Progress of Face Image Synthesis,2017 diff --git a/site/datasets/final/lfw.json b/site/datasets/final/lfw.json index d85818c6..ba64653a 100644 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