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diff --git a/site/datasets/unknown/youtube_faces.json b/site/datasets/unknown/youtube_faces.json index 4aa3b450..e10e3646 100644 --- a/site/datasets/unknown/youtube_faces.json +++ b/site/datasets/unknown/youtube_faces.json @@ -1 +1 @@ -{"id": "560e0e58d0059259ddf86fcec1fa7975dee6a868", "citations": [{"id": "2348f1fa2940b01ec90e023fac8cc96812189774", "title": "Face verification based on convolutional neural network and deep learning", "year": "2017", "pdf": []}, {"id": "28d4e027c7e90b51b7d8908fce68128d1964668a", "title": "Level Playing Field for Million Scale Face Recognition", "year": "2017", "pdf": []}, {"id": "38010ef51f34353d79d032991b703c1d158a9a16", "title": "A survey of image data indexing techniques", "year": "2018", "pdf": []}, {"id": "b2ae5c496fe01bb2e2dee107f75b82c6a2a23374", "title": "Attention-Based Template Adaptation for Face Verification", "year": "2017", "pdf": []}, {"id": "2e3d081c8f0e10f138314c4d2c11064a981c1327", "title": "A Comprehensive Performance Evaluation of 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"http://www.cse.msu.edu/~rossarun/pubs/RothLiuRossMetaxasKeystrokeAcoustics_TIFS2015.pdf", "http://www.cse.msu.edu/~rothjos1/papers/2015TIFS_Roth_Liu_Ross_Metaxas.pdf"]}, {"id": "9dfef52f45372ee76b63905606779080026dfeb1", "title": "The Best Practice of University and Community Cooperation in Open Source Software Project - TV Station Media Images Query System for Example", "year": "2018", "pdf": []}, {"id": "97865d31b5e771cf4162bc9eae7de6991ceb8bbf", "title": "Face and Gender Classification in Crowd Video", "year": "2015", "pdf": ["https://pdfs.semanticscholar.org/9786/5d31b5e771cf4162bc9eae7de6991ceb8bbf.pdf"]}, {"id": "533bfb82c54f261e6a2b7ed7d31a2fd679c56d18", "title": "Unconstrained Face Recognition: Identifying a Person of Interest From a Media Collection", "year": "2014", "pdf": ["http://biometrics.cse.msu.edu/Publications/Face/BestRowdenetal_UnconstrainedFaceRecognition_TIFS2014.pdf", "http://biometrics.cse.msu.edu/Publications/Face/BestRowdenetal_UnconstrainedFaceRecognition_TechReport_MSU-CSE-14-1.pdf"]}, {"id": "83447d47bb2837b831b982ebf9e63616742bfdec", "title": "An Automatic System for Unconstrained Video-Based Face Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1812.04058.pdf"]}, {"id": "406c5aeca71011fd8f8bd233744a81b53ccf635a", "title": "Scalable softmax loss for face verification", "year": "2017", "pdf": []}, {"id": "ff01bc3f49130d436fca24b987b7e3beedfa404d", "title": "Fuzzy System-Based Face Detection Robust to In-Plane Rotation Based on Symmetrical Characteristics of a Face", "year": "2016", "pdf": ["http://www.mdpi.com/2073-8994/8/8/75/pdf"]}, {"id": "b4f3e9fc0a2b40595ae0a625d1d768a57a7c2eba", "title": "Recognizing Disguised Faces in the Wild", "year": "2018", "pdf": ["https://arxiv.org/pdf/1811.08837.pdf"]}, {"id": "06aab105d55c88bd2baa058dc51fa54580746424", "title": "Image Set-Based Collaborative Representation for Face Recognition", 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"https://research-information.bristol.ac.uk/files/75922781/Ioannis_Pitas_Large_scale_classification_by_an_approximate_least_squares_one_class_support_vector_machine_ensemble_2015.pdf"]}, {"id": "a89cbc90bbb4477a48aec185f2a112ea7ebe9b4d", "title": "High Performance Large Scale Face Recognition with Multi-cognition Softmax and Feature Retrieval", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w27/Xu_High_Performance_Large_ICCV_2017_paper.pdf"]}, {"id": "d0a6a700779ac8cb70d7bb95f9a5afdda60152d9", "title": "Pyramid Mean Representation of Image Sequences for Fast Face Retrieval in Unconstrained Video Data", "year": "2014", "pdf": ["https://pdfs.semanticscholar.org/d0a6/a700779ac8cb70d7bb95f9a5afdda60152d9.pdf"]}, {"id": "021e008282714eaefc0796303f521c9e4f199d7e", "title": "NCC-Net: Normalized Cross Correlation Based Deep Matcher with Robustness to Illumination Variations", "year": "2018", "pdf": []}, {"id": "5c01d8bffb5cf7a5f871e3c691f8dc7dba6e6da9", "title": "Survey of biometric pattern recognition via machine learning techniques", "year": "2018", "pdf": ["http://www.m-hikari.com/ces/ces2018/ces33-36-2018/p/hernandezCES33-36-2018-2.pdf"]}, {"id": "88bee9733e96958444dc9e6bef191baba4fa6efa", "title": "Extending Face Identification to Open-Set Face Recognition", "year": "2014", "pdf": ["http://homepages.dcc.ufmg.br/~william/papers/paper_2014_SIBGRAPI.pdf"]}, {"id": "cbca355c5467f501d37b919d8b2a17dcb39d3ef9", "title": "Super-resolution of Very Low Resolution Faces from Videos", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/cbca/355c5467f501d37b919d8b2a17dcb39d3ef9.pdf"]}, {"id": "0fb45e704ef3ca1f9c70e7be3fb93b53714ed8b5", "title": "Head Pose and Expression Transfer Using Facial Status Score", "year": "2017", "pdf": []}, {"id": "098363b29eef1471c494382338687f2fe98f6e15", "title": "Metadata-Based Feature Aggregation Network for Face Recognition", "year": "2018", "pdf": []}, {"id": 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identification in near IR-videos using smart eye tracking profiles", "year": "2015", "pdf": []}, {"id": "5c54e0f46330787c4fac48aecced9a8f8e37658a", "title": "Simple Triplet Loss Based on Intra/Inter-Class Metric Learning for Face Verification", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w23/Ming_Simple_Triplet_Loss_ICCV_2017_paper.pdf"]}, {"id": "9f2984081ef88c20d43b29788fdf732ceabd5d6a", "title": "ClusterNet : Semi-Supervised Clustering using Neural Networks", "year": "2018", "pdf": []}, {"id": "70f189798c8b9f2b31c8b5566a5cf3107050b349", "title": "The challenge of face recognition from digital point-and-shoot cameras", "year": "2013", "pdf": ["http://biometrics.nist.gov/cs_links/face/PaSC/pasc2013_NISTIR.pdf", "http://www.cs.colostate.edu/~draper/papers/beveridge_btas13.pdf", "http://www.cs.colostate.edu/~vision/pasc/docs/pasc2013_NISTIR_061013.pdf", "http://www.cs.colostate.edu/~vision/publications/pasc2013_NISTIR_061013.pdf", 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"http://www.vision.ee.ethz.ch/~zzhiwu/papers/COX-Face-DB-TIP-final.pdf"]}, {"id": "f4ac6d29b6f544370d53aaff88c007c14a1fddfb", "title": "Changes in Facial Expression as Biometric: A Database and Benchmarks of Identification", "year": "2018", "pdf": ["http://sergioescalera.com/wp-content/uploads/2018/05/FG2018_Expression-Change-Biometrics.pdf", "http://vbn.aau.dk/files/279731010/FG2018_Expression_Biometric_CameraReady.pdf"]}, {"id": "973022a1f9e30a624f5e8f7158b5bbb114f4af32", "title": "Searching a specific person in a specific location using deep features", "year": "2016", "pdf": []}, {"id": "03f7041515d8a6dcb9170763d4f6debd50202c2b", "title": "Clustering Millions of Faces by Identity", "year": "2018", "pdf": ["https://arxiv.org/pdf/1604.00989.pdf"]}, {"id": "94f74c6314ffd02db581e8e887b5fd81ce288dbf", "title": "A Light CNN for Deep Face Representation With Noisy Labels", "year": "2018", "pdf": ["https://arxiv.org/pdf/1511.02683.pdf"]}, {"id": "57178b36c21fd7f4529ac6748614bb3374714e91", "title": "IARPA Janus Benchmark - C: Face Dataset and Protocol", "year": "2018", "pdf": []}, {"id": "d83583562f3536d5c13f8ca58925362f6878f5f4", "title": "Enhance Visual Recognition under Adverse Conditions via Deep Networks", "year": "2017", "pdf": ["https://arxiv.org/pdf/1712.07732.pdf"]}, {"id": "8da32ff9e3759dc236878ac240728b344555e4e9", "title": "Investigating Nuisance Factors in Face Recognition with DCNN Representation", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017_workshops/w6/papers/Ferrari_Investigating_Nuisance_Factors_CVPR_2017_paper.pdf"]}, {"id": "da141474d85257ae65e45b3d4b3a9aa23e62724d", "title": "Learning techniques for multi-modal facial analysis", "year": "2015", "pdf": []}, {"id": "c3a53b308c7a75c66759cbfdf52359d9be4f552b", "title": "On Detecting Partially Occluded Faces with Pose Variations", "year": "2017", "pdf": []}, {"id": "cfb8bc66502fb5f941ecdb22aec1fdbfdb73adce", "title": "Git Loss for Deep Face Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1807.08512.pdf"]}, {"id": "b8dba0504d6b4b557d51a6cf4de5507141db60cf", "title": "Comparing Performances of Big Data Stream Processing Platforms with RAM3S", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/b8db/a0504d6b4b557d51a6cf4de5507141db60cf.pdf"]}, {"id": "cdae8e9cc9d605856cf5709b2fdf61f722d450c1", "title": "Deep Learning for Biometrics : A Survey KALAIVANI SUNDARARAJAN", "year": "2018", "pdf": []}, {"id": "945ef646679b6c575d3bbef9c6fc0a9629ac1b62", "title": "Learning a structured dictionary for video-based face recognition", "year": "2016", "pdf": []}, {"id": "0aebe97a92f590bdf21cdadfddec8061c682cdb2", "title": "Probabilistic Elastic Part Model: A Pose-Invariant Representation for Real-World Face Verification", "year": "2018", "pdf": []}, {"id": "6e9862146e7e081429da233960ba0dfa9e400fc2", "title": "Cross-Spectral Cross-Resolution Face Recognition in Videos", "year": "2017", "pdf": 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"https://research-information.bristol.ac.uk/files/75922781/Ioannis_Pitas_Large_scale_classification_by_an_approximate_least_squares_one_class_support_vector_machine_ensemble_2015.pdf"]}, {"id": "a89cbc90bbb4477a48aec185f2a112ea7ebe9b4d", "title": "High Performance Large Scale Face Recognition with Multi-cognition Softmax and Feature Retrieval", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w27/Xu_High_Performance_Large_ICCV_2017_paper.pdf"]}, {"id": "d0a6a700779ac8cb70d7bb95f9a5afdda60152d9", "title": "Pyramid Mean Representation of Image Sequences for Fast Face Retrieval in Unconstrained Video Data", "year": "2014", "pdf": ["https://pdfs.semanticscholar.org/d0a6/a700779ac8cb70d7bb95f9a5afdda60152d9.pdf"]}, {"id": "021e008282714eaefc0796303f521c9e4f199d7e", "title": "NCC-Net: Normalized Cross Correlation Based Deep Matcher with Robustness to Illumination Variations", "year": "2018", "pdf": []}, {"id": "5c01d8bffb5cf7a5f871e3c691f8dc7dba6e6da9", "title": "Survey of biometric pattern recognition via machine learning techniques", "year": "2018", "pdf": ["http://www.m-hikari.com/ces/ces2018/ces33-36-2018/p/hernandezCES33-36-2018-2.pdf"]}, {"id": "88bee9733e96958444dc9e6bef191baba4fa6efa", "title": "Extending Face Identification to Open-Set Face Recognition", "year": "2014", "pdf": ["http://homepages.dcc.ufmg.br/~william/papers/paper_2014_SIBGRAPI.pdf"]}, {"id": "cbca355c5467f501d37b919d8b2a17dcb39d3ef9", "title": "Super-resolution of Very Low Resolution Faces from Videos", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/cbca/355c5467f501d37b919d8b2a17dcb39d3ef9.pdf"]}, {"id": "0fb45e704ef3ca1f9c70e7be3fb93b53714ed8b5", "title": "Head Pose and Expression Transfer Using Facial Status Score", "year": "2017", "pdf": []}, {"id": "098363b29eef1471c494382338687f2fe98f6e15", "title": "Metadata-Based Feature Aggregation Network for Face Recognition", "year": "2018", "pdf": []}, {"id": "80d4cf7747abfae96328183dd1f84133023c2668", "title": "Face retrieval in face track using sparse representation", "year": "2018", "pdf": []}, {"id": "cc91001f9d299ad70deb6453d55b2c0b967f8c0d", "title": "Performance Enhancement of Face Recognition in Smart TV Using Symmetrical Fuzzy-Based Quality Assessment", "year": "2015", "pdf": ["https://pdfs.semanticscholar.org/cc91/001f9d299ad70deb6453d55b2c0b967f8c0d.pdf"]}, {"id": "a50fa5048c61209149de0711b5f1b1806b43da00", "title": "Deep Features for Recognizing Disguised Faces in the Wild", "year": "2018", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2018_workshops/papers/w1/Bansal_Deep_Features_for_CVPR_2018_paper.pdf"]}, {"id": "747fddd7345b60da121fc13c5440a18039b912e6", "title": "Improving Consistency and Correctness of Sequence Inpainting using Semantically Guided Generative Adversarial Network", "year": "2017", "pdf": ["https://arxiv.org/pdf/1711.06106.pdf"]}, {"id": "33b4dc370731535e39df8ce22fb43dd80d811dc4", "title": "Face identification in near IR-videos using smart eye tracking profiles", "year": "2015", "pdf": []}, {"id": "5c54e0f46330787c4fac48aecced9a8f8e37658a", "title": "Simple Triplet Loss Based on Intra/Inter-Class Metric Learning for Face Verification", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w23/Ming_Simple_Triplet_Loss_ICCV_2017_paper.pdf"]}, {"id": "9f2984081ef88c20d43b29788fdf732ceabd5d6a", "title": "ClusterNet : Semi-Supervised Clustering using Neural Networks", "year": "2018", "pdf": []}, {"id": "70f189798c8b9f2b31c8b5566a5cf3107050b349", "title": "The challenge of face recognition from digital point-and-shoot cameras", "year": "2013", "pdf": ["http://biometrics.nist.gov/cs_links/face/PaSC/pasc2013_NISTIR.pdf", "http://www.cs.colostate.edu/~draper/papers/beveridge_btas13.pdf", "http://www.cs.colostate.edu/~vision/pasc/docs/pasc2013_NISTIR_061013.pdf", "http://www.cs.colostate.edu/~vision/publications/pasc2013_NISTIR_061013.pdf", "http://www3.nd.edu/~kwb/BeveridgeEtAlBTAS_2013.pdf", "https://ws680.nist.gov/publication/get_pdf.cfm?pub_id=913139", "https://www3.nd.edu/~kwb/Beveridge_EtAl_BTAS_2013.pdf"]}, {"id": "d9c0310203179d5328c4f1475fa4d68c5f0c7324", "title": "Face Analysis in the Wild", "year": "2017", "pdf": []}, {"id": "d6bdc70d259b38bbeb3a78db064232b4b4acc88f", "title": "Video-Based Face Association and Identification", "year": "2017", "pdf": []}, {"id": "be21529c47b79b688b420c5e296086698ba11350", "title": "CNN-Based Multimodal Human Recognition in Surveillance Environments", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/be21/529c47b79b688b420c5e296086698ba11350.pdf"]}, {"id": "9458c518a6e2d40fb1d6ca1066d6a0c73e1d6b73", "title": "A Benchmark and Comparative Study of Video-Based Face Recognition on COX Face Database", "year": "2015", "pdf": ["http://vipl.ict.ac.cn/sites/default/files/people/attach/Revision_COX_TIP_v3.0_1.pdf", "http://www.vision.ee.ethz.ch/~zzhiwu/papers/COX-Face-DB-TIP-final.pdf"]}, {"id": "f4ac6d29b6f544370d53aaff88c007c14a1fddfb", "title": "Changes in Facial Expression as Biometric: A Database and Benchmarks of Identification", "year": "2018", "pdf": ["http://sergioescalera.com/wp-content/uploads/2018/05/FG2018_Expression-Change-Biometrics.pdf", "http://vbn.aau.dk/files/279731010/FG2018_Expression_Biometric_CameraReady.pdf"]}, {"id": "973022a1f9e30a624f5e8f7158b5bbb114f4af32", "title": "Searching a specific person in a specific location using deep features", "year": "2016", "pdf": []}, {"id": "03f7041515d8a6dcb9170763d4f6debd50202c2b", "title": "Clustering Millions of Faces by Identity", "year": "2018", "pdf": ["https://arxiv.org/pdf/1604.00989.pdf"]}, {"id": "94f74c6314ffd02db581e8e887b5fd81ce288dbf", "title": "A Light CNN for Deep Face Representation With Noisy Labels", "year": "2018", "pdf": ["https://arxiv.org/pdf/1511.02683.pdf"]}, {"id": "57178b36c21fd7f4529ac6748614bb3374714e91", "title": "IARPA Janus Benchmark - C: Face Dataset and Protocol", "year": "2018", "pdf": []}, {"id": "d83583562f3536d5c13f8ca58925362f6878f5f4", "title": "Enhance Visual Recognition under Adverse Conditions via Deep Networks", "year": "2017", "pdf": ["https://arxiv.org/pdf/1712.07732.pdf"]}, {"id": "8da32ff9e3759dc236878ac240728b344555e4e9", "title": "Investigating Nuisance Factors in Face Recognition with DCNN Representation", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017_workshops/w6/papers/Ferrari_Investigating_Nuisance_Factors_CVPR_2017_paper.pdf"]}, {"id": "da141474d85257ae65e45b3d4b3a9aa23e62724d", "title": "Learning techniques for multi-modal facial analysis", "year": "2015", "pdf": []}, {"id": "c3a53b308c7a75c66759cbfdf52359d9be4f552b", "title": "On Detecting Partially Occluded Faces with Pose Variations", "year": "2017", "pdf": []}, {"id": "cfb8bc66502fb5f941ecdb22aec1fdbfdb73adce", "title": "Git Loss for Deep Face Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1807.08512.pdf"]}, {"id": "b8dba0504d6b4b557d51a6cf4de5507141db60cf", "title": "Comparing Performances of Big Data Stream Processing Platforms with RAM3S", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/b8db/a0504d6b4b557d51a6cf4de5507141db60cf.pdf"]}, {"id": "cdae8e9cc9d605856cf5709b2fdf61f722d450c1", "title": "Deep Learning for Biometrics : A Survey KALAIVANI SUNDARARAJAN", "year": "2018", "pdf": []}, {"id": "945ef646679b6c575d3bbef9c6fc0a9629ac1b62", "title": "Learning a structured dictionary for video-based face recognition", "year": "2016", "pdf": []}, {"id": "0aebe97a92f590bdf21cdadfddec8061c682cdb2", "title": "Probabilistic Elastic Part Model: A Pose-Invariant Representation for Real-World Face Verification", "year": "2018", "pdf": []}, {"id": "6e9862146e7e081429da233960ba0dfa9e400fc2", "title": "Cross-Spectral Cross-Resolution Face Recognition in Videos", "year": "2017", "pdf": 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"cd6e32b00a53310f90a7138a41b855bf44129637", "title": "Persons-In-Places: a Deep Features Based Approach for Searching a Specific Person in a Specific Location", "year": "2017", "pdf": []}, {"id": "36bb5cca0f6a75be8e66f58cba214b90982ee52f", "title": "A Quantum Probability Inspired Framework for Image-Set Based Face Identification", "year": "2017", "pdf": []}, {"id": "d00c335fbb542bc628642c1db36791eae24e02b7", "title": "Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/d00c/335fbb542bc628642c1db36791eae24e02b7.pdf"]}, {"id": "a52a69bf304d49fba6eac6a73c5169834c77042d", "title": "Margin Loss: Making Faces More Separable", "year": "2018", "pdf": []}, {"id": "0b6f110b702552858454347cadf22ddd1a05f62f", "title": "Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art", "year": "2018", "pdf": ["https://arxiv.org/pdf/1806.05226.pdf"]}, {"id": "f294278e03868257bfce132b8cf189359ada915a", "title": "Boosting Face in Video Recognition via CNN Based Key Frame Extraction", "year": "2018", "pdf": ["https://www.clarkson.edu/sites/default/files/2018-03/Boosting%20Face%20in%20Video%20Recognition%20via%20CNN%20based%20Key%20Frame%20Extraction.pdf"]}, {"id": "224d0eee53c2aa5d426d2c9b7fa5d843a47cf1db", "title": "Probabilistic Elastic Matching for Pose Variant Face Verification", "year": "2013", "pdf": ["http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/IEEE_CVPR2013/data/Papers/4989d499.pdf", "http://www.cv-foundation.org/openaccess/content_cvpr_2013/papers/Li_Probabilistic_Elastic_Matching_2013_CVPR_paper.pdf", "http://www.ifp.illinois.edu/~jyang29/papers/CVPR13-PEM.pdf"]}, {"id": "284d8ffb2f2d3bc9f793b82f8b7f75f2751b05d7", "title": "Disguised Faces in the Wild", "year": "2018", "pdf": ["http://iab-rubric.org/papers/2018_CVPRW_disguised-faces-wild.pdf", 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Deep Neural Network", "year": "2018", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2018_workshops/papers/w39/Xu_Using_Psychophysical_Methods_CVPR_2018_paper.pdf"]}, {"id": "5a1255d65e8309131638b3eb94aad5c52ab3629a", "title": "Improving Open Source Face Detection by Combining an Adapted Cascade Classification Pipeline and Active Learning", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/5a12/55d65e8309131638b3eb94aad5c52ab3629a.pdf"]}, {"id": "d44a93027208816b9e871101693b05adab576d89", "title": "On the Capacity of Face Representation", "year": "2017", "pdf": ["https://arxiv.org/pdf/1709.10433.pdf"]}, {"id": "c1f05b723e53ac4eb1133249b445c0011d42ca79", "title": "Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review", "year": "2017", "pdf": []}, {"id": "f60070d3a4d333aa1436e4c372b1feb5b316a7ba", "title": "Face Recognition via Centralized Coordinate Learning", "year": "2018", "pdf": ["https://arxiv.org/pdf/1801.05678.pdf"]}, {"id": 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Data", "year": "2015", "pdf": ["http://akme-a2.iosb.fraunhofer.de/EatThisGoogleScholar/d/2015_Face%20retrieval%20on%20large-scale%20video%20data.pdf"]}, {"id": "bec0c33d330385d73a5b6a05ad642d6954a6d632", "title": "Ranking, clustering and fusing the normalized LBP temporal facial features for face recognition in video sequences", "year": "2017", "pdf": []}, {"id": "e13360cda1ebd6fa5c3f3386c0862f292e4dbee4", "title": "Range Loss for Deep Face Recognition with Long-Tailed Training Data", "year": "2016", "pdf": ["https://arxiv.org/pdf/1611.08976.pdf"]}, {"id": "30fd7b1f8502b1c1d7a855946d99d2d5323ec973", "title": "Big Data Analysis for 2 Media Production", "year": "2016", "pdf": ["https://pdfs.semanticscholar.org/30fd/7b1f8502b1c1d7a855946d99d2d5323ec973.pdf"]}, {"id": "13fd0a4d06f30a665fc0f6938cea6572f3b496f7", "title": "Regularized Extreme Learning Machine for Large-scale Media Content Analysis", "year": "2015", "pdf": 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"http://www.robots.ox.ac.uk/~vedaldi/assets/pubs/parkhi14compact.pdf", "http://www.robots.ox.ac.uk/~vgg/publications/2014/Parkhi14/parkhi14.pdf"]}, {"id": "d31328b12eef33e7722b8e5505d0f9d9abe2ffd9", "title": "Deep Unsupervised Domain Adaptation for Face Recognition", "year": "2018", "pdf": []}, {"id": "0d3b167b52e9f0bf509e3af003ea320e6070b665", "title": "Two-level algorithm of facial expressions classification on complex background", "year": "2017", "pdf": []}, {"id": "727d03100d4a8e12620acd7b1d1972bbee54f0e6", "title": "von Mises-Fisher Mixture Model-based Deep learning: Application to Face Verification", "year": "2017", "pdf": ["https://arxiv.org/pdf/1706.04264.pdf"]}, {"id": "7079c51423ff61a18692da993ce3113451bf262a", "title": "Face recognition in unconstrained images and videos", "year": "2013", "pdf": ["https://pdfs.semanticscholar.org/7079/c51423ff61a18692da993ce3113451bf262a.pdf"]}, {"id": "76cd5e43df44e389483f23cb578a9015d1483d70", "title": "Face Verification from Depth using Privileged Information", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/76cd/5e43df44e389483f23cb578a9015d1483d70.pdf"]}, {"id": "7fa00c81f7c2d8da1551334b0e7bc3d7fd43130c", "title": "Deep Reconstruction Models for Image Set Classification", "year": "2015", "pdf": []}, {"id": "0cb2dd5f178e3a297a0c33068961018659d0f443", "title": "IARPA Janus Benchmark-B Face Dataset", "year": "2017", "pdf": []}, {"id": "9ba4a5e0b7bf6e26563d294f1f3de44d95b7f682", "title": "To Frontalize or Not to Frontalize: Do We Really Need Elaborate Pre-processing to Improve Face Recognition?", "year": "2018", "pdf": ["http://docs.wixstatic.com/ugd/445e27_b7f15ceb15d34e45836f98d9eeba9a78.pdf", "https://arxiv.org/pdf/1610.04823v1.pdf"]}, {"id": "3cd5b1d71c1d6a50fcc986589f2d0026c68d9803", "title": "On Sifts and Their Scales Lihi Zelnik-manor Technion", "year": "2012", "pdf": ["https://pdfs.semanticscholar.org/3cd5/b1d71c1d6a50fcc986589f2d0026c68d9803.pdf"]}, {"id": "60643bdab1c6261576e6610ea64ea0c0b200a28d", 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