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Diffstat (limited to 'site/datasets/citations/umd_faces.json')
| -rw-r--r-- | site/datasets/citations/umd_faces.json | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/site/datasets/citations/umd_faces.json b/site/datasets/citations/umd_faces.json index 4309a071..36e62c36 100644 --- a/site/datasets/citations/umd_faces.json +++ b/site/datasets/citations/umd_faces.json @@ -1 +1 @@ -{"id": "447d8893a4bdc29fa1214e53499ffe67b28a6db5", "paper": {"paperId": "447d8893a4bdc29fa1214e53499ffe67b28a6db5", "key": "umd_faces", "title": "Electronic Transport in Quantum Confined Systems", "journal": "", "address": "", "address_type": "", "lat": "", "lng": "", "pdf_link": "http://pdfs.semanticscholar.org/447d/8893a4bdc29fa1214e53499ffe67b28a6db5.pdf", "report_link": "papers/447d8893a4bdc29fa1214e53499ffe67b28a6db5.html", "citation_count": 1, "citations_geocoded": 0, "citations_unknown": 1, "citations_empty": 0, "citations_pdf": 1, "citations_doi": 0, "name": "UMD"}, "address": null, "citations": []}
\ No newline at end of file +{"id": "71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6", "paper": {"paperId": "71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6", "key": "umd_faces", "title": "The Do\u2019s and Don\u2019ts for CNN-Based Face Verification", "journal": "2017 IEEE International Conference on Computer Vision Workshops (ICCVW)", "address": "", "address_type": "", "lat": "", "lng": "", "pdf_link": "https://arxiv.org/pdf/1705.07426.pdf", "report_link": "papers/71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6.html", "citation_count": 25, "citations_geocoded": 8, "citations_unknown": 17, "citations_empty": 3, "citations_pdf": 17, "citations_doi": 6, "name": "UMD"}, "address": null, "citations": [["Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans", "University of Maryland, College Park, Maryland 20740 United States", "University of Maryland", "University of Maryland", "The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA", "39.28996850", "-76.62196103", "edu", "", 2018], ["Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model", "", "University of Surrey", "University of Surrey", "University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK", "51.24303255", "-0.59001382", "edu", "", "2018"], ["Investigating Nuisances in DCNN-Based Face Recognition", "Department of Information Engineering, University of Florence, Florence, Italy", "University of Florence", "University of Florence", "Piazza di San Marco, 4, 50121 Firenze FI, Italy", "43.77764260", "11.25976500", "edu", "", "2018"], ["Deep Face Recognition: A Survey", "", "Beijing University of Posts and Telecommunications", "Beijing University of Posts and Telecommunications", "\u5317\u4eac\u90ae\u7535\u5927\u5b66, \u897f\u571f\u57ce\u8def, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100082, \u4e2d\u56fd", "39.96014880", "116.35193921", "edu", "", "2018"], ["Fast Face Image Synthesis with Minimal Training.", "", "University of Notre Dame", "University of Notre Dame", "University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA", "41.70456775", "-86.23822026", "edu", "", "2018"], ["VGGFace2: A Dataset for Recognising Faces across Pose and Age", "", "University of Oxford", "University of Oxford", "Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK", "51.75345380", "-1.25400997", "edu", "", "2018"], ["Disentangling 3D Pose in a Dendritic CNN for Unconstrained 2D Face Alignment", "", "University of Maryland College Park", "University of Maryland College Park", "University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA", "38.99203005", "-76.94610290", "edu", "", "2018"], ["UV-GAN: Adversarial Facial UV Map Completion for Pose-Invariant 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", "", "2018"]]}
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