{"id":"https://openalex.org/W4399658730","doi":"https://doi.org/10.1145/3641584.3641663","title":"Adapting CBAM and IAL to Bayesian Loss-based Crowd Counting","display_name":"Adapting CBAM and IAL to Bayesian Loss-based Crowd Counting","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4399658730","doi":"https://doi.org/10.1145/3641584.3641663"},"language":"en","primary_location":{"id":"doi:10.1145/3641584.3641663","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641584.3641663","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 6th International Conference on Artificial Intelligence and Pattern Recognition (AIPR)","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/A5007070184","display_name":"Huimin Du","orcid":"https://orcid.org/0009-0000-0562-2632"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huimin Du","raw_affiliation_strings":["Center for Image and Information Processing,School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0009-0000-0562-2632","affiliations":[{"raw_affiliation_string":"Center for Image and Information Processing,School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089434715","display_name":"Yu Hao","orcid":"https://orcid.org/0000-0002-6820-5243"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Hao","raw_affiliation_strings":["Center for Image and Information Processing,School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-6820-5243","affiliations":[{"raw_affiliation_string":"Center for Image and Information Processing,School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033600235","display_name":"Xiaoyang Zhang","orcid":"https://orcid.org/0009-0000-3383-7438"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyang Zhang","raw_affiliation_strings":["Center for Image and Information Processing,School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0009-0000-3383-7438","affiliations":[{"raw_affiliation_string":"Center for Image and Information Processing,School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100761763","display_name":"Ying Liu","orcid":"https://orcid.org/0000-0002-9037-7818"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Liu","raw_affiliation_strings":["Center for Image and Information Processing,School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-9037-7818","affiliations":[{"raw_affiliation_string":"Center for Image and Information Processing,School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29834983,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"530","last_page":"535"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9990000128746033,"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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/computer-science","display_name":"Computer science","score":0.6512842178344727},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5842952728271484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2917330265045166}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6512842178344727},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5842952728271484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2917330265045166}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3641584.3641663","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641584.3641663","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 6th International Conference on Artificial Intelligence and Pattern Recognition (AIPR)","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":19,"referenced_works":["https://openalex.org/W2122243179","https://openalex.org/W2207893099","https://openalex.org/W2340590112","https://openalex.org/W2463631526","https://openalex.org/W2768906052","https://openalex.org/W2798314446","https://openalex.org/W2810783540","https://openalex.org/W2883929025","https://openalex.org/W2886443245","https://openalex.org/W2963826106","https://openalex.org/W2964117779","https://openalex.org/W2967161970","https://openalex.org/W3018586778","https://openalex.org/W3027606690","https://openalex.org/W3097305524","https://openalex.org/W3176458063","https://openalex.org/W4221142499","https://openalex.org/W4312791242","https://openalex.org/W6681368121"],"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":{"Probability-originated":[0],"crowding":[1],"counting":[2,25,46],"strategy":[3],"has":[4],"advantages":[5],"of":[6,11,102,120],"providing":[7],"additional":[8],"spatial":[9],"information":[10],"pedestrians":[12],"and":[13,52,110,157],"smaller":[14],"model":[15,26],"scale.":[16],"This":[17],"paper":[18],"proposes":[19],"a":[20],"novel":[21],"Bayesian":[22],"Loss-based":[23],"crowd":[24,45,54],"which":[27],"integrates":[28],"the":[29,58,61,69,74,80,84,89,94,100,108,112,115,121,125,129,134,143,153],"Convolutional":[30],"Block":[31],"Attention":[32,36],"Module":[33],"(CBAM)and":[34],"Instance":[35],"Loss":[37],"(IAL)":[38],"to":[39,64,77,92],"further":[40],"address":[41],"typical":[42],"issues":[43],"in":[44,107,146],"such":[47],"as":[48,60,73],"complicated":[49],"background,":[50],"occlusion,":[51],"uneven":[53],"distribution.":[55],"After":[56],"adapting":[57],"VGG-19":[59],"front-end":[62],"network":[63,91],"efficiently":[65],"extract":[66],"visual":[67],"features,":[68],"CBAM":[70],"is":[71,131],"implemented":[72],"intermediate":[75],"process":[76],"concentrate":[78],"on":[79,138],"key":[81],"features":[82],"with":[83,124],"attention":[85],"mechanism,":[86],"before":[87],"using":[88],"back-end":[90],"output":[93],"predicted":[95],"density":[96],"map.":[97],"To":[98],"handle":[99],"deviation":[101,127],"manual":[103],"labeled":[104],"head":[105],"positions":[106],"dataset":[109],"improve":[111],"training":[113],"efficiency,":[114],"IAL":[116],"where":[117],"only":[118],"90%":[119],"annotation":[122],"points":[123],"smallest":[126],"from":[128],"prediction":[130],"adapted":[132],"by":[133,150],"approach.":[135],"Experiments":[136],"results":[137],"two":[139],"benchmarking":[140],"datasets":[141],"demonstrated":[142],"network's":[144],"efficiency":[145],"enhancing":[147],"headcount":[148],"accuracy":[149],"significantly":[151],"optimized":[152],"MAE(mean":[154],"absolute":[155],"error)":[156],"MSE(mean":[158],"square":[159],"error).":[160]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}