{"id":"https://openalex.org/W3096563782","doi":"https://doi.org/10.1109/tip.2020.3034487","title":"TJU-DHD: A Diverse High-Resolution Dataset for Object Detection","display_name":"TJU-DHD: A Diverse High-Resolution Dataset for Object Detection","publication_year":2020,"publication_date":"2020-11-03","ids":{"openalex":"https://openalex.org/W3096563782","doi":"https://doi.org/10.1109/tip.2020.3034487","mag":"3096563782","pmid":"https://pubmed.ncbi.nlm.nih.gov/33141669"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.3034487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3034487","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2011.09170","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yanwei Pang","orcid":"https://orcid.org/0000-0001-6670-3727"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanwei Pang","raw_affiliation_strings":["Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-6670-3727","affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiale Cao","orcid":"https://orcid.org/0000-0002-5160-6841"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiale Cao","raw_affiliation_strings":["Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-5160-6841","affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yazhao Li","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yazhao Li","raw_affiliation_strings":["Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jin Xie","orcid":"https://orcid.org/0000-0001-6978-8834"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Xie","raw_affiliation_strings":["Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-6978-8834","affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hanqing Sun","orcid":"https://orcid.org/0000-0002-8022-4172"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanqing Sun","raw_affiliation_strings":["Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-8022-4172","affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Brain-Inspired Intelligence Technology, School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jinfeng Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094894","display_name":"China Automotive Technology and Research Center","ror":"https://ror.org/00r5r6807","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210094894"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinfeng Gong","raw_affiliation_strings":["China Automotive Technology and Research Center Company Ltd., Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Automotive Technology and Research Center Company Ltd., Tianjin, China","institution_ids":["https://openalex.org/I4210094894"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.7154,"has_fulltext":false,"cited_by_count":88,"citation_normalized_percentile":{"value":0.96068764,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"30","issue":null,"first_page":"207","last_page":"219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9714999794960022,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9714999794960022,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.0066999997943639755,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.004999999888241291,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.8156999945640564},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.678600013256073},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6306999921798706},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5842999815940857},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5016999840736389},{"id":"https://openalex.org/keywords/object-class-detection","display_name":"Object-class detection","score":0.48910000920295715},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.43529999256134033},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.421999990940094},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.39480000734329224}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.8156999945640564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7718999981880188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6805999875068665},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.678600013256073},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6306999921798706},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5842999815940857},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5016999840736389},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4952999949455261},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.48910000920295715},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C182521987","wikidata":"https://www.wikidata.org/wiki/Q2493877","display_name":"Viola\u2013Jones object detection framework","level":5,"score":0.3310000002384186},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.32269999384880066},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.31299999356269836},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2867000102996826},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2750000059604645},{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2662000060081482}],"mesh":[{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005145","descriptor_name":"Face","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D005145","descriptor_name":"Face","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D005145","descriptor_name":"Face","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018986","descriptor_name":"Motor Vehicles","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018986","descriptor_name":"Motor Vehicles","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018986","descriptor_name":"Motor Vehicles","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D056667","descriptor_name":"Biometric Identification","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D056667","descriptor_name":"Biometric Identification","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D056667","descriptor_name":"Biometric Identification","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2020.3034487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3034487","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:33141669","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33141669","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:arXiv.org:2011.09170","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.09170","pdf_url":"https://arxiv.org/pdf/2011.09170","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2011.09170","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.09170","pdf_url":"https://arxiv.org/pdf/2011.09170","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G11847706","display_name":null,"funder_award_id":"61632018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1680407332","display_name":null,"funder_award_id":"2018AAA0102800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4445662794","display_name":null,"funder_award_id":"61906131","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":88,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2031454541","https://openalex.org/W2031489346","https://openalex.org/W2034025266","https://openalex.org/W2074777933","https://openalex.org/W2088049833","https://openalex.org/W2098699644","https://openalex.org/W2102605133","https://openalex.org/W2117539524","https://openalex.org/W2139479830","https://openalex.org/W2150066425","https://openalex.org/W2159386181","https://openalex.org/W2161969291","https://openalex.org/W2163352848","https://openalex.org/W2194775991","https://openalex.org/W2291533986","https://openalex.org/W2340897893","https://openalex.org/W2490270993","https://openalex.org/W2529780763","https://openalex.org/W2548197316","https://openalex.org/W2565639579","https://openalex.org/W2594507094","https://openalex.org/W2613599172","https://openalex.org/W2768489488","https://openalex.org/W2775890136","https://openalex.org/W2781228439","https://openalex.org/W2792824754","https://openalex.org/W2803740064","https://openalex.org/W2883363148","https://openalex.org/W2886904239","https://openalex.org/W2889709668","https://openalex.org/W2892614179","https://openalex.org/W2894299524","https://openalex.org/W2894820835","https://openalex.org/W2895077992","https://openalex.org/W2895451584","https://openalex.org/W2909593838","https://openalex.org/W2945786113","https://openalex.org/W2948672349","https://openalex.org/W2962917547","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963318220","https://openalex.org/W2963351448","https://openalex.org/W2963404857","https://openalex.org/W2963446712","https://openalex.org/W2963566548","https://openalex.org/W2963574614","https://openalex.org/W2963681621","https://openalex.org/W2963769056","https://openalex.org/W2963786238","https://openalex.org/W2963998989","https://openalex.org/W2964010755","https://openalex.org/W2964241181","https://openalex.org/W2970390221","https://openalex.org/W2981927700","https://openalex.org/W2982769033","https://openalex.org/W2982770724","https://openalex.org/W2984009799","https://openalex.org/W2985405845","https://openalex.org/W2986357608","https://openalex.org/W2988452521","https://openalex.org/W2989604896","https://openalex.org/W2990075400","https://openalex.org/W2990130718","https://openalex.org/W2990631821","https://openalex.org/W2997344726","https://openalex.org/W3000764918","https://openalex.org/W3004894036","https://openalex.org/W3034638324","https://openalex.org/W3034955056","https://openalex.org/W3092873533","https://openalex.org/W3097096317","https://openalex.org/W6607458078","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6662335928","https://openalex.org/W6676338569","https://openalex.org/W6684191040","https://openalex.org/W6750697433","https://openalex.org/W6751325469","https://openalex.org/W6753494528","https://openalex.org/W6755965428","https://openalex.org/W6760424586","https://openalex.org/W6776110894","https://openalex.org/W6785652829","https://openalex.org/W6788995615"],"related_works":[],"abstract_inverted_index":{"Vehicles,":[0],"pedestrians,":[1],"and":[2,8,18,44,85,99,103,134,146,159,173,199,206,226],"riders":[3],"are":[4,92,209],"the":[5,12,22,37,59,76,80,89,95,101,104,110,162,187,192,214,221],"most":[6],"important":[7,28,49],"interesting":[9],"objects":[10,29,150],"for":[11],"perception":[13],"modules":[14],"of":[15,25,39,97,131,140],"self-driving":[16],"vehicles":[17],"video":[19],"surveillance.":[20],"However,":[21],"state-of-the-art":[23],"performance":[24],"detecting":[26],"such":[27,65],"(esp.":[30],"small":[31],"objects)":[32],"is":[33,183,235],"far":[34],"from":[35,70,88],"satisfying":[36],"demand":[38],"practical":[40],"systems.":[41],"Large-scale,":[42],"rich-diversity,":[43],"high-resolution":[45,116,124],"datasets":[46,64,82],"play":[47],"an":[48],"role":[50],"in":[51,94,151,157,168,229],"developing":[52],"better":[53],"object":[54,204,224],"detection":[55,205,208,225,228],"methods":[56],"to":[57,108],"satisfy":[58],"demand.":[60],"Existing":[61],"public":[62],"large-scale":[63],"as":[66],"MS":[67],"COCO":[68],"collected":[69,87],"websites":[71],"do":[72],"not":[73],"focus":[74],"on":[75,223],"specific":[77,90],"scenarios.":[78],"Moreover,":[79],"popular":[81],"(e.g.,":[83],"KITTI":[84],"Citypersons)":[86],"scenarios":[91],"limited":[93],"number":[96],"images":[98,125,127,136],"instances,":[100],"resolution,":[102],"diversity.":[105],"To":[106],"attempt":[107],"solve":[109],"problem,":[111],"we":[112],"build":[113],"a":[114,129,138,154,165,178],"diverse":[115,180],"dataset":[117,121,163,182,217,234],"(called":[118],"TJU-DHD).":[119],"The":[120,233],"contains":[122],"115354":[123],"(52%":[126],"have":[128,137],"resolution":[130,139],"1624\u00d71200":[132],"pixels":[133],"48%":[135],"at":[141,237],"least":[142],"2,":[143],"560\u00d71.440":[144],"pixels)":[145],"709":[147],"330":[148],"labeled":[149],"total":[152],"with":[153],"large":[155],"variance":[156],"scale":[158],"appearance.":[160],"Meanwhile,":[161],"has":[164],"rich":[166],"diversity":[167],"season":[169],"variance,":[170,172],"illumination":[171],"weather":[174],"variance.":[175],"In":[176],"addition,":[177],"new":[179],"pedestrian":[181,207,227],"further":[184],"built.":[185],"With":[186],"four":[188],"different":[189],"detectors":[190],"(i.e.,":[191],"one-stage":[193],"RetinaNet,":[194],"anchor-free":[195],"FCOS,":[196],"two-stage":[197],"FPN,":[198],"Cascade":[200],"R-CNN),":[201],"experiments":[202],"about":[203],"conducted.":[210],"We":[211],"hope":[212],"that":[213],"newly":[215],"built":[216],"can":[218],"help":[219],"promote":[220],"research":[222],"these":[230],"two":[231],"scenes.":[232],"available":[236],"https://github.com/tjubiit/TJU-DHD.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":10}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2020-11-09T00:00:00"}
