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diff --git a/site/datasets/citations/apis.json b/site/datasets/citations/apis.json index 6467e07f..b364f8ad 100644 --- a/site/datasets/citations/apis.json +++ b/site/datasets/citations/apis.json @@ -1 +1 @@ -{"id": "488e475eeb3bb39a145f23ede197cd3620f1d98a", "paper": {"paperId": "488e475eeb3bb39a145f23ede197cd3620f1d98a", "key": "apis", "title": "Pedestrian Attribute Classification in Surveillance: Database and Evaluation", "journal": "2013 IEEE International Conference on Computer Vision Workshops", "address": "", "country": "", "address_type": "", "lat": "", "lng": "", "pdf_link": "http://www.cbsr.ia.ac.cn/english/APiS_1.0_paper.pdf", "report_link": "papers/488e475eeb3bb39a145f23ede197cd3620f1d98a.html", "citation_count": 26, "citations_geocoded": 18, "citations_unknown": 8, "citations_empty": 1, "citations_pdf": 13, "citations_doi": 13, "name": "APiS1.0"}, "address": null, "citations": [["Person re-identification using CNN features learned from combination of attributes", "Faculty of Information Science and Electrical Engineering (ISEE), Kyushu University, Japan", "Kyushu University", "Kyushu University", "\u4f0a\u90fd\u30b2\u30b9\u30c8\u30cf\u30a6\u30b9, \u685c\u4e95\u592a\u90ce\u4e38\u7dda, \u897f\u533a, \u798f\u5ca1\u5e02, \u798f\u5ca1\u770c, \u4e5d\u5dde\u5730\u65b9, 819\u22120395, \u65e5\u672c", "33.59914655", "130.22359848", "edu", "", "Japan", "2016"], ["Deep View-Sensitive Pedestrian Attribute Inference in an end-to-end Model", "", "Karlsruhe Institute of Technology", "Karlsruhe Institute of Technology", "KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-W\u00fcrttemberg, 76351, Deutschland", "49.10184375", "8.43312560", "edu", "", "Germany", "2017"], ["Pedestrian Attribute Recognition At Far Distance", "", "Chinese University of Hong Kong", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2014"], ["Analysing Soft Clothing Biometrics for Retrieval", "", "University of Southampton", "University of Southampton", "Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK", "50.89273635", "-1.39464295", "edu", "", "United Kingdom", "2014"], ["Pedestrian gender classification using combined global and local parts-based convolutional neural networks", "Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang, Malaysia", "Universiti Tunku Abdul Rahman", "Universiti Tunku Abdul Rahman", "Jalan Universiti, Bandar Barat, 31900 Kampar, Negeri Perak, Malaysia", "4.34006730", "101.14297990", "edu", "", "Malaysia", "2018"], ["Pedestrian Attribute Detection using CNN", "", "Stanford University", "Stanford University", "Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA", "37.43131385", "-122.16936535", "edu", "", "United States", "2016"], ["From Clothing to Identity: Manual and Automatic Soft Biometrics", "School of Electronics and Computer Science, University of Southampton, Southampton, U.K.", "University of Southampton", "University of Southampton", "Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK", "50.89273635", "-1.39464295", "edu", "", "United Kingdom", "2016"], ["Attribute Recognition by Joint Recurrent Learning of Context and Correlation", "", "Queen Mary University of London", "Queen Mary University of London", "Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK", "51.52472720", "-0.03931035", "edu", "", "United Kingdom", "2017"], ["Deep domain adaptation for describing people based on fine-grained clothing attributes", "", "IBM Research, North Carolina", "IBM Research", "IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA", "35.90422720", "-78.85565763", "company", "", "United States", "2015"], ["A hybrid approach to pedestrian clothing color attribute extraction", "OMRON Social Solutions Co. 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\ No newline at end of file |