{"id":"https://openalex.org/W3108815824","doi":"https://doi.org/10.1109/tip.2020.3040854","title":"Mask-Guided Attention Network and Occlusion-Sensitive Hard Example Mining for Occluded Pedestrian Detection","display_name":"Mask-Guided Attention Network and Occlusion-Sensitive Hard Example Mining for Occluded Pedestrian Detection","publication_year":2020,"publication_date":"2020-12-05","ids":{"openalex":"https://openalex.org/W3108815824","doi":"https://doi.org/10.1109/tip.2020.3040854","mag":"3108815824","pmid":"https://pubmed.ncbi.nlm.nih.gov/33275581"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.3040854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3040854","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":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089409762","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":"https://openalex.org/A5086887025","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":"https://openalex.org/A5032830353","display_name":"Muhammad Haris Khan","orcid":"https://orcid.org/0000-0001-9746-276X"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Muhammad Haris Khan","raw_affiliation_strings":["Computer Vision Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022929869","display_name":"Rao Muhammad Anwer","orcid":"https://orcid.org/0000-0002-9041-2214"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Rao Muhammad Anwer","raw_affiliation_strings":["Computer Vision Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0002-9041-2214","affiliations":[{"raw_affiliation_string":"Computer Vision Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100760570","display_name":"Fahad Shahbaz Khan","orcid":"https://orcid.org/0000-0002-4263-3143"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Fahad Shahbaz Khan","raw_affiliation_strings":["Computer Vision Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082634513","display_name":"Ling Shao","orcid":"https://orcid.org/0000-0002-8264-6117"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Ling Shao","raw_affiliation_strings":["Computer Vision Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0002-8264-6117","affiliations":[{"raw_affiliation_string":"Computer Vision Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9708,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.92918693,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"30","issue":null,"first_page":"3872","last_page":"3884"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.7440761923789978},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7329100370407104},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7124603986740112},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.66204833984375},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5364011526107788},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5358138680458069},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5222659707069397},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5139281749725342},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.47161558270454407},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4322812855243683},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4297158718109131},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.4147474467754364},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4133094847202301},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39208608865737915},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08755040168762207}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.7440761923789978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7329100370407104},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7124603986740112},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.66204833984375},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5364011526107788},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5358138680458069},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5222659707069397},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5139281749725342},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.47161558270454407},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4322812855243683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4297158718109131},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.4147474467754364},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4133094847202301},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39208608865737915},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08755040168762207},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":"Q000145","qualifier_name":"classification","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":"D014741","descriptor_name":"Video Recording","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014741","descriptor_name":"Video Recording","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014741","descriptor_name":"Video Recording","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":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","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":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2020.3040854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3040854","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:33275581","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33275581","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}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"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"}],"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":71,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1475617732","https://openalex.org/W1495267108","https://openalex.org/W1522301498","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1765260417","https://openalex.org/W1903127635","https://openalex.org/W2031454541","https://openalex.org/W2044291182","https://openalex.org/W2083896825","https://openalex.org/W2098064689","https://openalex.org/W2098699644","https://openalex.org/W2108598243","https://openalex.org/W2140090057","https://openalex.org/W2150385913","https://openalex.org/W2156547346","https://openalex.org/W2170101770","https://openalex.org/W2194775991","https://openalex.org/W2200528286","https://openalex.org/W2291533986","https://openalex.org/W2490270993","https://openalex.org/W2497039038","https://openalex.org/W2531915888","https://openalex.org/W2594507094","https://openalex.org/W2609144136","https://openalex.org/W2613599172","https://openalex.org/W2743905801","https://openalex.org/W2775890136","https://openalex.org/W2792824754","https://openalex.org/W2799199435","https://openalex.org/W2803973142","https://openalex.org/W2883363148","https://openalex.org/W2884030607","https://openalex.org/W2884561390","https://openalex.org/W2894820835","https://openalex.org/W2895077992","https://openalex.org/W2895451584","https://openalex.org/W2896540732","https://openalex.org/W2962721361","https://openalex.org/W2963150697","https://openalex.org/W2963315052","https://openalex.org/W2963318220","https://openalex.org/W2963404857","https://openalex.org/W2963516811","https://openalex.org/W2963681621","https://openalex.org/W2963769056","https://openalex.org/W2963998989","https://openalex.org/W2964121744","https://openalex.org/W2974603289","https://openalex.org/W2984933298","https://openalex.org/W2988098865","https://openalex.org/W2989676862","https://openalex.org/W2990075400","https://openalex.org/W2990130718","https://openalex.org/W2995649684","https://openalex.org/W2997344726","https://openalex.org/W3001652308","https://openalex.org/W3034955056","https://openalex.org/W3092873533","https://openalex.org/W3098140381","https://openalex.org/W3104732503","https://openalex.org/W3106250896","https://openalex.org/W3110568504","https://openalex.org/W6620707391","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6682360581","https://openalex.org/W6752196072","https://openalex.org/W6785436334","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W3122828758","https://openalex.org/W2101960027","https://openalex.org/W4205958986","https://openalex.org/W2197846993","https://openalex.org/W49697837","https://openalex.org/W2586575957","https://openalex.org/W2972620127","https://openalex.org/W2981141433"],"abstract_inverted_index":{"Pedestrian":[0],"detection":[1,67,86,133],"relying":[2],"on":[3,18,23,92,160,172,194],"deep":[4],"convolution":[5],"neural":[6],"networks":[7],"has":[8],"made":[9],"significant":[10],"progress.":[11],"Though":[12],"promising":[13],"results":[14,193],"have":[15],"been":[16],"achieved":[17],"standard":[19],"pedestrians,":[20],"the":[21,69,98,109,124,132,190,195,202],"performance":[22],"heavily":[24,196],"occluded":[25,65,99,138,197],"pedestrians":[26,39],"remains":[27],"far":[28],"from":[29],"satisfactory.":[30],"The":[31],"main":[32],"culprits":[33],"are":[34,158,209],"intra-class":[35],"occlusions":[36,42],"involving":[37],"other":[38,45],"and":[40,50,115,127,163,207],"inter-class":[41],"caused":[43],"by":[44,101],"objects,":[46],"such":[47],"as":[48],"cars":[49],"bicycles.":[51],"These":[52],"result":[53],"in":[54,184],"a":[55,75,169],"multitude":[56],"of":[57,182,201],"occlusion":[58,125],"patterns.":[59],"We":[60],"propose":[61,108],"an":[62,179],"approach":[63,167,177],"for":[64],"pedestrian":[66,85,94,199],"with":[68,189],"following":[70],"contributions.":[71],"First,":[72],"we":[73,107,141],"introduce":[74],"novel":[76],"mask-guided":[77],"attention":[78,89],"network":[79,90],"that":[80,118,144],"fits":[81],"naturally":[82],"into":[83],"popular":[84],"pipelines.":[87],"Our":[88,166,176],"emphasizes":[91],"visible":[93],"regions":[95],"while":[96],"suppressing":[97],"ones":[100],"modulating":[102],"full":[103],"body":[104],"features.":[105],"Second,":[106],"occlusion-sensitive":[110,116],"hard":[111,120],"example":[112],"mining":[113],"method":[114],"loss":[117],"mines":[119],"samples":[121],"according":[122],"to":[123,131,152],"level":[126],"assigns":[128],"higher":[129],"weights":[130],"errors":[134],"occurring":[135],"at":[136],"highly":[137],"pedestrians.":[139],"Third,":[140],"empirically":[142],"demonstrate":[143],"weak":[145],"box-based":[146],"segmentation":[147],"annotations":[148],"provide":[149],"reasonable":[150],"approximation":[151],"their":[153],"dense":[154],"pixel-wise":[155],"counterparts.":[156],"Experiments":[157],"performed":[159],"CityPersons,":[161],"Caltech":[162],"ETH":[164],"datasets.":[165,175],"sets":[168],"new":[170],"state-of-the-art":[171],"all":[173],"three":[174],"obtains":[178],"absolute":[180],"gain":[181],"10.3%":[183],"log-average":[185],"miss":[186],"rate,":[187],"compared":[188],"best":[191],"reported":[192],"HO":[198],"set":[200],"CityPersons":[203],"test":[204],"set.":[205],"Code":[206],"models":[208],"available":[210],"at:":[211],"https://github.com/Leotju/MGAN.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}