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-{"id": "6dcf418c778f528b5792104760f1fbfe90c6dd6a", "paper": {"paperId": "6dcf418c778f528b5792104760f1fbfe90c6dd6a", "key": "agedb", "title": "AgeDB: The First Manually Collected, In-the-Wild Age Database", "journal": "2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)", "address": "", "country": "", "address_type": "", "lat": "", "lng": "", "pdf_link": "https://ibug.doc.ic.ac.uk/media/uploads/documents/agedb.pdf", "report_link": "papers/6dcf418c778f528b5792104760f1fbfe90c6dd6a.html", "citation_count": 11, "citations_geocoded": 10, "citations_unknown": 1, "citations_empty": 0, "citations_pdf": 10, "citations_doi": 1, "name": "AgeDB"}, "address": null, "citations": [["Marginal Loss for Deep Face Recognition", "", "Imperial College London", "Imperial College London", "Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK", "51.49887085", "-0.17560797", "edu", "", "United Kingdom", "2017"], ["Longitudinal Face Aging in the Wild - Recent Deep Learning Approaches", "", "Concordia University", "Concordia University", "Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA", "45.57022705", "-122.63709346", "edu", "", "United States", "2018"], ["Speeding-Up Age Estimation in Intelligent Demographics System via Network Optimization", "", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "Singapore", "2018"], ["ArcFace: Additive Angular Margin Loss for Deep Face Recognition", "", "Imperial College London", "Imperial College London", "Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK", "51.49887085", "-0.17560797", "edu", "", "United Kingdom", "2018"], ["Multi-Attribute Robust Component Analysis for Facial UV Maps", "", "University of London", "University of London", "Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK", "51.52176680", "-0.13019072", "edu", "", "United Kingdom", "2018"], ["Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition", "", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", "China", "2018"], ["Visual Data Augmentation through Learning", "", "Middlesex University", "Middlesex University", "Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK", "51.59029705", "-0.22963221", "edu", "", "United Kingdom", "2018"], ["MobileFaceNets: Efficient CNNs for Accurate Real-time Face Verification on Mobile Devices", "", "Beijing Jiaotong University", "Beijing Jiaotong University", "\u5317\u4eac\u4ea4\u901a\u5927\u5b66, \u94f6\u674f\u5927\u9053, \u7a3b\u9999\u56ed\u5357\u793e\u533a, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100044, \u4e2d\u56fd", "39.94976005", "116.33629046", "edu", "", "China", "2018"], ["Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition", "", "Tencent", "Tencent AI Lab, China", "Ke Ji Zhong Yi Lu, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057", "22.54471540", "113.93571640", "company", "Keji Middle 1st Rd, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057", "China", "2018"], ["Recovering Joint and Individual Components in Facial Data", "Onfido, London, United Kingdom", "Onfido, London, United Kingdom", "Onfido, London, United Kingdom", "3 Finsbury Ave, London EC2M 2PA, UK", "51.51981120", "-0.08412990", "company", "", "United Kingdom", "2018"]]} \ No newline at end of file
+{"id": "6dcf418c778f528b5792104760f1fbfe90c6dd6a", "paper": {"key": "agedb", "name": "AgeDB", "title": "AgeDB: The First Manually Collected, In-the-Wild Age Database", "year": "2017"}, "address": {}, "citations": [{"id": "40bb090a4e303f11168dce33ed992f51afe02ff7", "title": "Marginal Loss for Deep Face Recognition", "addresses": [{"name": "Imperial College London", "source_name": "Imperial College London", "street_adddress": "Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK", "lat": "51.49887085", "lng": "-0.17560797", "type": "edu", "country": "United Kingdom"}], "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/Deng_Marginal_Loss_for_CVPR_2017_paper.pdf"]}, {"id": "ec05078be14a11157ac0e1c6b430ac886124589b", "title": "Longitudinal Face Aging in the Wild - Recent Deep Learning Approaches", "addresses": [{"name": "Concordia University", "source_name": 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at end of file