{"id":"https://openalex.org/W3210983250","doi":"https://doi.org/10.1109/tpami.2021.3124956","title":"Locating and Counting Heads in Crowds With a Depth Prior","display_name":"Locating and Counting Heads in Crowds With a Depth Prior","publication_year":2021,"publication_date":"2021-11-04","ids":{"openalex":"https://openalex.org/W3210983250","doi":"https://doi.org/10.1109/tpami.2021.3124956","mag":"3210983250","pmid":"https://pubmed.ncbi.nlm.nih.gov/34735337"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2021.3124956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2021.3124956","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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":null,"display_name":"Dongze Lian","orcid":"https://orcid.org/0000-0002-4947-0316"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongze Lian","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4947-0316","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xianing Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianing Chen","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jing Li","orcid":"https://orcid.org/0000-0001-7027-7513"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-7027-7513","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Weixin Luo","orcid":"https://orcid.org/0000-0002-0754-6458"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixin Luo","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-0754-6458","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":null,"display_name":"Shenghua Gao","orcid":"https://orcid.org/0000-0003-1626-2040"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghua Gao","raw_affiliation_strings":["Shanghai Engineering Research Center of Intelligent Vision and Imaging, Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1626-2040","affiliations":[{"raw_affiliation_string":"Shanghai Engineering Research Center of Intelligent Vision and Imaging, Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":3.7667,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.94792618,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"44","issue":"12","first_page":"9056","last_page":"9072"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.6171000003814697,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.6171000003814697,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.061000000685453415,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.044199999421834946,"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/initialization","display_name":"Initialization","score":0.6834999918937683},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.6804999709129333},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.6345000267028809},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5116000175476074},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48750001192092896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47350001335144043},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.4553999900817871},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4465999901294708}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7748000025749207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7074999809265137},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6834999918937683},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.6804999709129333},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.6345000267028809},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5116000175476074},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.510699987411499},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48750001192092896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47350001335144043},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.4553999900817871},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4465999901294708},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.415800005197525},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.35199999809265137},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.31869998574256897},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2768000066280365}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2021.3124956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2021.3124956","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:34735337","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34735337","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 pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:hub.hku.hk:10722/345152","is_oa":false,"landing_page_url":"https://hub.hku.hk/handle/10722/345152","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"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":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1306822220","display_name":null,"funder_award_id":"#61932020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3429630933","display_name":null,"funder_award_id":"20ZR1436000","funder_id":"https://openalex.org/F4320321885","funder_display_name":"Science and Technology Commission of Shanghai Municipality"},{"id":"https://openalex.org/G4118779427","display_name":null,"funder_award_id":"2018AAA0100704","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/F4320321659","display_name":"Shanghai Education Development Foundation","ror":"https://ror.org/02kq92y46"},{"id":"https://openalex.org/F4320321881","display_name":"Shanghai Municipal Education Commission","ror":"https://ror.org/05tewj457"},{"id":"https://openalex.org/F4320321885","display_name":"Science and Technology Commission of Shanghai Municipality","ror":"https://ror.org/03kt66j61"},{"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":96,"referenced_works":["https://openalex.org/W607748843","https://openalex.org/W1203557841","https://openalex.org/W1565402342","https://openalex.org/W1910776219","https://openalex.org/W2002142942","https://openalex.org/W2013039598","https://openalex.org/W2049338372","https://openalex.org/W2072232009","https://openalex.org/W2094950164","https://openalex.org/W2108598243","https://openalex.org/W2115579991","https://openalex.org/W2120815373","https://openalex.org/W2123175289","https://openalex.org/W2146352414","https://openalex.org/W2147221461","https://openalex.org/W2150066425","https://openalex.org/W2168195382","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2463631526","https://openalex.org/W2519281173","https://openalex.org/W2520723410","https://openalex.org/W2541389513","https://openalex.org/W2565639579","https://openalex.org/W2729018917","https://openalex.org/W2739974641","https://openalex.org/W2741077351","https://openalex.org/W2765278422","https://openalex.org/W2798490576","https://openalex.org/W2886443245","https://openalex.org/W2894846593","https://openalex.org/W2895051362","https://openalex.org/W2904814274","https://openalex.org/W2948467257","https://openalex.org/W2948513880","https://openalex.org/W2949333977","https://openalex.org/W2955171701","https://openalex.org/W2962720716","https://openalex.org/W2963035940","https://openalex.org/W2963231953","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2963693541","https://openalex.org/W2963786238","https://openalex.org/W2963838390","https://openalex.org/W2963893037","https://openalex.org/W2964047820","https://openalex.org/W2964121718","https://openalex.org/W2964203052","https://openalex.org/W2964209782","https://openalex.org/W2964238416","https://openalex.org/W2964307651","https://openalex.org/W2964721919","https://openalex.org/W2966271765","https://openalex.org/W2967069910","https://openalex.org/W2967776630","https://openalex.org/W2969620138","https://openalex.org/W2971927438","https://openalex.org/W2981436300","https://openalex.org/W2981918755","https://openalex.org/W2982007926","https://openalex.org/W2982014038","https://openalex.org/W2982130202","https://openalex.org/W2985314571","https://openalex.org/W2987988567","https://openalex.org/W2988452521","https://openalex.org/W2990946490","https://openalex.org/W2991203386","https://openalex.org/W2996703886","https://openalex.org/W2997135920","https://openalex.org/W3004672782","https://openalex.org/W3011158920","https://openalex.org/W3015469128","https://openalex.org/W3025164301","https://openalex.org/W3027606690","https://openalex.org/W3035304632","https://openalex.org/W3045455261","https://openalex.org/W3049248796","https://openalex.org/W3084883754","https://openalex.org/W3151111735","https://openalex.org/W3176458063","https://openalex.org/W6631190155","https://openalex.org/W6639102338","https://openalex.org/W6674662834","https://openalex.org/W6681368121","https://openalex.org/W6722836162","https://openalex.org/W6726497184","https://openalex.org/W6736057607","https://openalex.org/W6747654920","https://openalex.org/W6750254146","https://openalex.org/W6756040250","https://openalex.org/W6763278908","https://openalex.org/W6771590690","https://openalex.org/W6773441890","https://openalex.org/W6776069494","https://openalex.org/W6776331362"],"related_works":["https://openalex.org/W1891287906","https://openalex.org/W2755342338","https://openalex.org/W2036807459","https://openalex.org/W1969923398","https://openalex.org/W4286377598","https://openalex.org/W2167578145","https://openalex.org/W2134367902","https://openalex.org/W2140020088","https://openalex.org/W2248546716","https://openalex.org/W2338631224"],"abstract_inverted_index":{"To":[0],"simultaneously":[1],"estimate":[2],"the":[3,34,56,63,66,80,133,174,180,230,240,256,262,277,287,317],"number":[4],"of":[5,36,68,119,135,155,157,170,207],"heads":[6,9,104,156],"and":[7,23,74,122,160,201,224,276,294,309,324],"locate":[8],"with":[10,187,250],"bounding":[11,181],"boxes,":[12],"we":[13,42,111,139,178,211,243],"resort":[14],"to":[15,32,54,88,101,131,146,152,189,260,303],"detection-based":[16,37],"crowd":[17,216,292,307],"counting":[18,217,280,293,308,323],"by":[19],"leveraging":[20],"RGB-D":[21,196,215,274,279,291],"data":[22,259],"design":[24],"a":[25,44,69,72,75,114,124,142,148,161,221,225,246],"dual-path":[26],"guided":[27,47,127],"detection":[28,48,60,121,144,175],"network":[29,61],"(DPDNet).":[30],"Specifically,":[31],"improve":[33,55,132],"performance":[35,205,289,315],"approaches":[38],"for":[39,93,117,167,204,290,320],"dense/tiny":[40],"heads,":[41,138],"propose":[43,123,141,245],"density":[45,52,64,91,96,115,125],"map":[46,53,92,97,116,126],"module,":[49],"which":[50,219,253],"leverages":[51],"head/non-head":[57],"classification":[58],"in":[59,82,173,239],"where":[62],"implies":[65],"probability":[67],"pixel":[70],"being":[71,106],"head,":[73],"depth-adaptive":[76],"kernel":[77],"that":[78,194,283],"considers":[79],"variances":[81],"head":[83,120,322],"sizes":[84,172,184],"is":[85,164],"also":[86,140],"introduced":[87],"generate":[89,147],"high-fidelity":[90],"more":[94],"robust":[95],"regression.":[98],"In":[99],"order":[100],"prevent":[102],"dense":[103],"from":[105],"filtered":[107],"out":[108],"during":[109],"post-processing,":[110],"utilize":[112],"such":[113],"post-processing":[118],"NMS":[128],"strategy.":[129],"Meanwhile,":[130],"ability":[134],"detecting":[136],"small":[137,200],"depth-guided":[143],"module":[145],"dynamic":[149],"dilated":[150],"convolution":[151],"extract":[153],"features":[154],"different":[158],"scales,":[159],"depth-aware":[162],"anchor":[163,171],"further":[165,244],"designed":[166],"better":[168,314],"initialization":[169],"framework.":[176],"Then":[177],"use":[179],"boxes":[182],"whose":[183],"are":[185,198],"generated":[186],"depth":[188,231,247,258,263],"train":[190],"our":[191,271,284,297],"DPDNet.":[192],"Considering":[193],"existing":[195],"datasets":[197,275,319],"too":[199],"not":[202],"suitable":[203],"evaluation":[206],"data-driven":[208],"based":[209,306],"approaches,":[210],"collect":[212],"two":[213,273],"large-scale":[214],"datasets,":[218],"comprise":[220],"synthetic":[222,257],"dataset":[223,281],"real-world":[226,241],"dataset,":[227,242],"respectively.":[228],"Since":[229],"value":[232,264],"at":[233,265],"long-distance":[234,266],"positions":[235],"cannot":[236],"be":[237,300],"obtained":[238],"completion":[248],"method":[249,285,298],"meta":[251],"learning,":[252],"fully":[254],"utilizes":[255],"complete":[261],"positions.":[267],"Extensive":[268],"experiments":[269],"on":[270,316],"proposed":[272],"MICC":[278],"show":[282],"achieves":[286,310],"best":[288],"localization.":[295,325],"Further,":[296],"can":[299],"easily":[301],"extended":[302],"RGB":[304,318],"image":[305],"comparable":[311],"or":[312],"even":[313],"both":[321]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":6}],"updated_date":"2026-07-09T07:52:08.696243","created_date":"2021-11-08T00:00:00"}