{"id":"https://openalex.org/W2999780639","doi":"https://doi.org/10.1145/3338533.3366687","title":"Multi-Dilation Network for Crowd Counting","display_name":"Multi-Dilation Network for Crowd Counting","publication_year":2019,"publication_date":"2019-12-15","ids":{"openalex":"https://openalex.org/W2999780639","doi":"https://doi.org/10.1145/3338533.3366687","mag":"2999780639"},"language":"en","primary_location":{"id":"doi:10.1145/3338533.3366687","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3338533.3366687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Multimedia Asia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5101797017","display_name":"Shuheng Wang","orcid":"https://orcid.org/0009-0005-4107-5038"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuheng Wang","raw_affiliation_strings":["Department of Computer Science and Technology, Tongji University, Shanghai, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tongji University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058982350","display_name":"Hanli Wang","orcid":"https://orcid.org/0000-0002-9999-4871"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanli Wang","raw_affiliation_strings":["Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5119247506","display_name":"Qinyu Li","orcid":"https://orcid.org/0000-0003-0862-4451"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinyu Li","raw_affiliation_strings":["Department of Computer Science and Technology, Tongji University, Shanghai, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tongji University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dilation","display_name":"Dilation (metric space)","score":0.8481853008270264},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6790066361427307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.656823992729187},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5464377403259277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.546271800994873},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5343443751335144},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5065301656723022},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.49162107706069946},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.43775659799575806},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.4334956705570221},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.3607678711414337},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2283426821231842},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16147178411483765}],"concepts":[{"id":"https://openalex.org/C2780757906","wikidata":"https://www.wikidata.org/wiki/Q5276676","display_name":"Dilation (metric space)","level":2,"score":0.8481853008270264},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6790066361427307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.656823992729187},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5464377403259277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.546271800994873},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5343443751335144},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5065301656723022},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.49162107706069946},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.43775659799575806},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.4334956705570221},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3607678711414337},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2283426821231842},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16147178411483765},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3338533.3366687","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3338533.3366687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Multimedia Asia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8500000238418579,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W815611303","https://openalex.org/W1686810756","https://openalex.org/W2065994824","https://openalex.org/W2079023123","https://openalex.org/W2145983039","https://openalex.org/W2151666244","https://openalex.org/W2207893099","https://openalex.org/W2412782625","https://openalex.org/W2517615595","https://openalex.org/W2729018917","https://openalex.org/W2963717945","https://openalex.org/W2965247173","https://openalex.org/W4240153047"],"related_works":["https://openalex.org/W4247388746","https://openalex.org/W2314720829","https://openalex.org/W3178576217","https://openalex.org/W4221063543","https://openalex.org/W4285794683","https://openalex.org/W4385195237","https://openalex.org/W4286256617","https://openalex.org/W4385577504","https://openalex.org/W4318676890","https://openalex.org/W121055840"],"abstract_inverted_index":{"With":[0],"the":[1,16,36,51,94,150,158,181,203],"growth":[2],"of":[3,18,23,30,38,46,96,107],"urban":[4],"population,":[5],"crowd":[6,24,31,68,97,172],"analysis":[7],"has":[8,133],"become":[9],"an":[10,41],"important":[11],"and":[12,57,118,176,197],"necessary":[13],"task":[14],"in":[15,40,99,142],"field":[17],"computer":[19],"vision.":[20],"The":[21,102,167],"goal":[22],"counting,":[25],"which":[26,136,208],"is":[27,33,62,90,104,162],"a":[28,44,47,110,119,130,192],"subfield":[29],"analysis,":[32],"to":[34,50,66,80,92,125,139,202,212],"count":[35],"number":[37],"people":[39],"image":[42],"or":[43],"zone":[45],"picture.":[48],"Due":[49],"problems":[52],"like":[53],"heavy":[54],"occlusions,":[55],"perspective":[56],"luminous":[58],"intensity":[59],"variations,":[60],"it":[61],"still":[63,163,216],"extremely":[64],"challenging":[65,171],"achieve":[67],"counting.":[69],"Recent":[70],"state-of-the-art":[71,189],"approaches":[72],"are":[73,137],"mainly":[74],"designed":[75],"with":[76,191,205,220],"convolutional":[77,148],"neural":[78],"networks":[79],"generate":[81,126],"density":[82,127],"maps.":[83,128],"In":[84],"this":[85],"work,":[86],"Multi-Dilation":[87],"Network":[88],"(MDNet)":[89],"proposed":[91,182],"solve":[93],"problem":[95],"counting":[98,173],"congested":[100],"scenes.":[101],"MDNet":[103,183,215],"made":[105],"up":[106],"two":[108,170],"parts:":[109],"VGG-16":[111],"based":[112],"front":[113],"end":[114,121],"for":[115],"feature":[116],"extraction":[117],"back":[120],"containing":[122],"multi-dilation":[123,131,151],"blocks":[124,207],"Especially,":[129],"block":[132,152],"four":[134],"branches":[135],"used":[138],"collect":[140],"features":[141,156],"different":[143],"sizes.":[144],"By":[145],"using":[146],"dilated":[147],"operations,":[149],"could":[153],"obtain":[154],"various":[155],"while":[157],"maximum":[159],"kernel":[160],"size":[161],"3":[164],"x":[165],"3.":[166],"experiments":[168],"on":[169],"datasets,":[174],"UCF_CC_50":[175],"ShanghaiTech,":[177],"have":[178],"shown":[179],"that":[180],"achieves":[184],"better":[185],"performances":[186,219],"than":[187],"other":[188],"methods,":[190],"lower":[193],"mean":[194,198],"absolute":[195],"error":[196],"squared":[199],"error.":[200],"Comparing":[201],"network":[204],"multi-scale":[206],"adopt":[209],"larger":[210],"kernels":[211],"extract":[213],"features,":[214],"gains":[217],"competitive":[218],"fewer":[221],"model":[222],"parameters.":[223]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}