{"id":"https://openalex.org/W4402916630","doi":"https://doi.org/10.1109/icip51287.2024.10648039","title":"Spatial-Channel Collaborated Attention for Cross-Scale Crowd Counting","display_name":"Spatial-Channel Collaborated Attention for Cross-Scale Crowd Counting","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402916630","doi":"https://doi.org/10.1109/icip51287.2024.10648039"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10648039","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10648039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","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/A5005269268","display_name":"Yongpeng Chang","orcid":"https://orcid.org/0000-0003-2593-7732"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongpeng Chang","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065404863","display_name":"Guangchun Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I4400573310","display_name":"Hangzhou City University","ror":"https://ror.org/01wck0s05","country_code":null,"type":"education","lineage":["https://openalex.org/I4400573310"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangchun Gao","raw_affiliation_strings":["Hangzhou City University,School of Information and Electrical Engineering,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou City University,School of Information and Electrical Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I4400573310"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"2536","last_page":"2542"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9945999979972839,"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":0.9945999979972839,"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":0.9945999979972839,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.989799976348877,"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/computer-science","display_name":"Computer science","score":0.6075665354728699},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.575808584690094},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5393242239952087},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.17298248410224915},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1503562331199646},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1320100724697113}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6075665354728699},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.575808584690094},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5393242239952087},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.17298248410224915},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1503562331199646},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1320100724697113}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10648039","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10648039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2042322506","https://openalex.org/W2155916750","https://openalex.org/W2194775991","https://openalex.org/W2463631526","https://openalex.org/W2517615595","https://openalex.org/W2752782242","https://openalex.org/W2886443245","https://openalex.org/W2895051362","https://openalex.org/W2963035940","https://openalex.org/W2963091558","https://openalex.org/W2964209782","https://openalex.org/W2967069910","https://openalex.org/W3015469128","https://openalex.org/W3087861058","https://openalex.org/W3092787802","https://openalex.org/W3094502228","https://openalex.org/W3096609285","https://openalex.org/W3097305524","https://openalex.org/W3138516171","https://openalex.org/W3170841864","https://openalex.org/W3176458063","https://openalex.org/W3190723141","https://openalex.org/W3203845557","https://openalex.org/W4225264236","https://openalex.org/W4289752563","https://openalex.org/W4295312788","https://openalex.org/W4313182800","https://openalex.org/W4385245566","https://openalex.org/W4390873023","https://openalex.org/W4393148727","https://openalex.org/W6637373629","https://openalex.org/W6766978945","https://openalex.org/W6783507135"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Large-scale":[0],"variations":[1,66],"in":[2,34,67],"crowd":[3,9,27,68,76,135],"images":[4],"pose":[5],"significant":[6],"challenges":[7],"to":[8,21,60,105,121],"counting.":[10,69],"Recently,":[11],"the":[12,30,35,62,75,80,84,99,123,127,148],"widely":[13],"adopted":[14],"vision":[15],"Transformer":[16],"has":[17],"been":[18],"extensively":[19],"used":[20],"extract":[22],"spatial":[23,108],"cross-scale":[24,47,107],"features":[25,33,85,112],"from":[26],"images.":[28],"However,":[29],"interaction":[31],"of":[32,64,74,83,126,150],"channel":[36],"dimension":[37],"is":[38],"frequently":[39],"overlooked,":[40],"despite":[41],"its":[42],"potential":[43],"benefits":[44],"for":[45],"learning":[46],"features.":[48,109],"In":[49],"this":[50],"paper,":[51],"we":[52,78,97],"introduce":[53],"a":[54,117],"Spatial-Channel":[55],"Collaborated":[56],"Attention":[57,90],"Network":[58],"(SCCAN)":[59],"address":[61],"challenge":[63],"large-scale":[65],"Specifically,":[70],"given":[71],"feature":[72],"maps":[73],"image,":[77],"exploit":[79],"inter-channel":[81],"correlation":[82],"through":[86],"parallel":[87],"Channel":[88,93],"Pooling":[89],"(CPA)":[91],"and":[92,142],"Self-Attention":[94,103],"(CSA).":[95],"Then":[96],"utilize":[98],"proposed":[100],"Scale-aware":[101],"Window":[102],"(SWSA)":[104],"learn":[106],"The":[110,144],"extracted":[111],"are":[113],"subsequently":[114],"fed":[115],"into":[116],"convolutional":[118],"regression":[119],"head":[120],"predict":[122],"density":[124],"map":[125],"crowd.":[128],"We":[129],"conduct":[130],"extensive":[131],"experiments":[132],"on":[133],"public":[134],"counting":[136],"datasets":[137],"including":[138],"ShanghaiTech":[139],"A,":[140],"UCF-QNRF,":[141],"JHU++.":[143],"experimental":[145],"results":[146],"demonstrate":[147],"superiority":[149],"our":[151],"method.":[152]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}