{"id":"https://openalex.org/W2981802706","doi":"https://doi.org/10.1145/3343031.3350914","title":"Crowd Counting via Multi-layer Regression","display_name":"Crowd Counting via Multi-layer Regression","publication_year":2019,"publication_date":"2019-10-15","ids":{"openalex":"https://openalex.org/W2981802706","doi":"https://doi.org/10.1145/3343031.3350914","mag":"2981802706"},"language":"en","primary_location":{"id":"doi:10.1145/3343031.3350914","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3350914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","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/A5080281882","display_name":"Xin Tan","orcid":"https://orcid.org/0000-0001-9346-1196"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Tan","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028561002","display_name":"Chun Min Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Tao","raw_affiliation_strings":["Nanjing Tech University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084591510","display_name":"Tongwei Ren","orcid":"https://orcid.org/0000-0003-3092-424X"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongwei Ren","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035112538","display_name":"Jinhui Tang","orcid":"https://orcid.org/0000-0001-9008-222X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101546753","display_name":"Gangshan Wu","orcid":"https://orcid.org/0000-0003-1391-1762"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gangshan Wu","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5080281882"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":1.7368,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.88230843,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1907","last_page":"1915"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"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":0.9927999973297119,"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/computer-science","display_name":"Computer science","score":0.6892281770706177},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.6533697247505188},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6006285548210144},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5832406878471375},{"id":"https://openalex.org/keywords/degree","display_name":"Degree (music)","score":0.5342985987663269},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5217127203941345},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5104590654373169},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.4838177561759949},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44389280676841736},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26013684272766113},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23918583989143372},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20659688115119934}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6892281770706177},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.6533697247505188},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6006285548210144},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5832406878471375},{"id":"https://openalex.org/C2775997480","wikidata":"https://www.wikidata.org/wiki/Q586277","display_name":"Degree (music)","level":2,"score":0.5342985987663269},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5217127203941345},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5104590654373169},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.4838177561759949},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44389280676841736},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26013684272766113},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23918583989143372},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20659688115119934},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3343031.3350914","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3350914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1903029394","https://openalex.org/W1910776219","https://openalex.org/W2031454541","https://openalex.org/W2072232009","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2123175289","https://openalex.org/W2143043044","https://openalex.org/W2145983039","https://openalex.org/W2161969291","https://openalex.org/W2168356304","https://openalex.org/W2183341477","https://openalex.org/W2207893099","https://openalex.org/W2463631526","https://openalex.org/W2510012886","https://openalex.org/W2514654788","https://openalex.org/W2517615595","https://openalex.org/W2519281173","https://openalex.org/W2520826941","https://openalex.org/W2788040570","https://openalex.org/W2895051362","https://openalex.org/W2949162858","https://openalex.org/W2952888378","https://openalex.org/W2962676885","https://openalex.org/W2962720716","https://openalex.org/W2962835968","https://openalex.org/W2963035940","https://openalex.org/W2963693541","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W2963893037","https://openalex.org/W2964203052","https://openalex.org/W3097096317"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"Crowd":[0],"counting":[1,34,177],"aims":[2],"to":[3,102,123,140],"estimate":[4,141],"the":[5,54,58,62,70,91,96,106,125,137,181],"number":[6],"of":[7,43,61,155],"persons":[8],"in":[9,64,161,175],"a":[10,31,44,65,103,152],"crowd":[11,33,66,76,93,111,130,142,145,176],"image--a":[12],"challenge":[13],"until":[14],"this":[15,27],"day--as":[16],"congestion":[17,59,86,98],"degree":[18,60,99],"varies,":[19],"people's":[20],"appearances":[21],"may":[22],"seem":[23],"different.":[24],"To":[25,133],"address":[26],"problem,":[28],"we":[29],"propose":[30],"novel":[32],"method":[35,139],"named":[36],"Multi-layer":[37],"Regression":[38],"Network":[39],"(MRNet),":[40],"which":[41],"consists":[42],"multi-layer":[45,169],"recognition":[46,55],"branch":[47,56],"and":[48,74,179],"several":[49,75],"density":[50,108,112,116,127,131],"regressors.":[51,149],"In":[52,88],"practice,":[53],"recognizes":[57],"regions":[63,77,82,94,146],"image,":[67],"then":[68],"disintegrates":[69],"image":[71],"into":[72],"background":[73],"layer":[78],"by":[79],"layer,":[80,90],"each":[81,89],"are":[83,100,121],"assigned":[84],"different":[85,148],"degrees.":[87],"recognized":[92],"with":[95,105,147,163],"specific":[97],"delivered":[101],"regressor":[104],"corresponding":[107],"prior":[109],"for":[110,129],"estimation.":[113,132],"The":[114],"generated":[115],"maps":[117],"at":[118],"all":[119],"layers":[120],"integrated":[122],"obtain":[124],"final":[126],"map":[128],"date,":[134],"MRNet":[135,156,171],"is":[136],"first":[138],"densities":[143],"on":[144,157],"We":[150],"conduct":[151],"comprehensive":[153],"evaluation":[154],"four":[158],"typical":[159],"datasets":[160],"comparison":[162],"nine":[164],"state-of-the-art":[165,182],"methods.":[166,183],"By":[167],"using":[168],"regression,":[170],"achieves":[172],"significant":[173],"improvement":[174],"accuracy,":[178],"outperforms":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":9}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}