{"id":"https://openalex.org/W4386902848","doi":"https://doi.org/10.1109/tcsvt.2023.3317518","title":"Progressive Multi-Resolution Loss for Crowd Counting","display_name":"Progressive Multi-Resolution Loss for Crowd Counting","publication_year":2023,"publication_date":"2023-09-20","ids":{"openalex":"https://openalex.org/W4386902848","doi":"https://doi.org/10.1109/tcsvt.2023.3317518"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2023.3317518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2023.3317518","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Circuits and Systems for Video Technology","raw_type":"journal-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/A5106743656","display_name":"Ziheng Yan","orcid":"https://orcid.org/0009-0003-7428-558X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziheng Yan","raw_affiliation_strings":["Key Laboratory of Big Data Mining and Knowledge Management, School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Mining and Knowledge Management, School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070842891","display_name":"Yuankai Qi","orcid":"https://orcid.org/0000-0003-4312-5682"},"institutions":[{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]},{"id":"https://openalex.org/I5681781","display_name":"The University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yuankai Qi","raw_affiliation_strings":["Australian Institute for Machine Learning, The University of Adelaide, Adelaide, SA, Australia"],"affiliations":[{"raw_affiliation_string":"Australian Institute for Machine Learning, The University of Adelaide, Adelaide, SA, Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I5681781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100775216","display_name":"Guorong Li","orcid":"https://orcid.org/0000-0003-3954-2387"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guorong Li","raw_affiliation_strings":["Key Laboratory of Big Data Mining and Knowledge Management, School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Mining and Knowledge Management, School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100439402","display_name":"Xinyan Liu","orcid":"https://orcid.org/0000-0003-2638-4324"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyan Liu","raw_affiliation_strings":["Key Laboratory of Big Data Mining and Knowledge Management, School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Mining and Knowledge Management, School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014774434","display_name":"Weigang Zhang","orcid":"https://orcid.org/0000-0003-0042-7074"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weigang Zhang","raw_affiliation_strings":["Harbin Institute of Technology, Weihai, China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Weihai, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418319","display_name":"Ming\u2013Hsuan Yang","orcid":"https://orcid.org/0000-0003-4848-2304"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming-Hsuan Yang","raw_affiliation_strings":["EECS, University of California at Merced, Merced, CA, USA"],"affiliations":[{"raw_affiliation_string":"EECS, University of California at Merced, Merced, CA, USA","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028597017","display_name":"Qingming Huang","orcid":"https://orcid.org/0000-0001-7542-296X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingming Huang","raw_affiliation_strings":["Key Laboratory of Big Data Mining and Knowledge Management, School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Mining and Knowledge Management, School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5106743656"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":2.6479,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.91927764,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"34","issue":"5","first_page":"3232","last_page":"3244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9993000030517578,"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":0.9966999888420105,"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":0.5533353686332703},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.474112331867218},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4573513865470886},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4326780438423157}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5533353686332703},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.474112331867218},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4573513865470886},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4326780438423157}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2023.3317518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2023.3317518","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5967673014","display_name":null,"funder_award_id":"61976069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6212863906","display_name":null,"funder_award_id":"U21B2038","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7528510259","display_name":null,"funder_award_id":"61836002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8752815154","display_name":null,"funder_award_id":"62272438","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W2088929512","https://openalex.org/W2194775991","https://openalex.org/W2197234429","https://openalex.org/W2463631526","https://openalex.org/W2541389513","https://openalex.org/W2612114597","https://openalex.org/W2741077351","https://openalex.org/W2793254521","https://openalex.org/W2793477525","https://openalex.org/W2886443245","https://openalex.org/W2895051362","https://openalex.org/W2961566087","https://openalex.org/W2963231953","https://openalex.org/W2963693541","https://openalex.org/W2964209782","https://openalex.org/W2965247173","https://openalex.org/W2966893608","https://openalex.org/W2967069910","https://openalex.org/W2969079301","https://openalex.org/W2982007926","https://openalex.org/W2982014038","https://openalex.org/W2982130202","https://openalex.org/W2996703886","https://openalex.org/W3004672782","https://openalex.org/W3007175960","https://openalex.org/W3015469128","https://openalex.org/W3027606690","https://openalex.org/W3035307763","https://openalex.org/W3084883754","https://openalex.org/W3087861058","https://openalex.org/W3097305524","https://openalex.org/W3109157205","https://openalex.org/W3126329292","https://openalex.org/W3138516171","https://openalex.org/W3176458063","https://openalex.org/W3201782689","https://openalex.org/W3203845557","https://openalex.org/W4205490223","https://openalex.org/W4205890571","https://openalex.org/W4214828374","https://openalex.org/W4280510608","https://openalex.org/W4283312418","https://openalex.org/W4304098313","https://openalex.org/W4312443924","https://openalex.org/W4312613051","https://openalex.org/W4312791242","https://openalex.org/W4312826597","https://openalex.org/W4375868813","https://openalex.org/W4382567984","https://openalex.org/W4382998741","https://openalex.org/W4386076535","https://openalex.org/W6637373629","https://openalex.org/W6681368121","https://openalex.org/W6783507135","https://openalex.org/W6785789763"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Crowd":[0],"counting":[1,152],"is":[2,12,88,112,124],"usually":[3],"handled":[4],"in":[5],"a":[6,40,67,113,127],"density":[7,21,45,57,79,100],"map":[8,22,58],"regression":[9],"fashion,":[10],"which":[11],"supervised":[13],"via":[14,66],"an":[15],"L2":[16,32,110,129],"loss":[17,33,70,87,111,137],"between":[18,43],"the":[19,56,92,97,107,135],"predicted":[20,44],"and":[23,46,133,142,160,165],"ground":[24],"truth.":[25],"To":[26],"effectively":[27],"regulate":[28],"models,":[29],"various":[30],"improved":[31],"functions":[34],"have":[35],"been":[36],"developed":[37],"to":[38,54,126,146],"find":[39,105],"better":[41],"correspondence":[42],"annotation":[47],"positions.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52],"propose":[53],"predict":[55],"at":[59,71,81,170],"one":[60],"resolution":[61],"but":[62],"measure":[63],"its":[64],"quality":[65],"derived":[68,118],"log-formed":[69],"multiple":[72],"resolutions.":[73],"Unlike":[74],"existing":[75],"methods":[76,148],"that":[77,106],"assume":[78],"maps":[80,101],"different":[82],"resolutions":[83],"are":[84,168],"independent,":[85],"our":[86,117],"obtained":[89],"by":[90,96],"modeling":[91],"likelihood":[93],"function":[94],"inspired":[95],"relationship":[98],"of":[99,116],"across":[102],"multi-resolutions.":[103],"We":[104,120],"traditional":[108],"single-resolution":[109,128],"particular":[114],"case":[115],"log-likelihood.":[119],"mathematically":[121],"prove":[122],"it":[123],"superior":[125],"loss.":[130],"Without":[131],"bells":[132],"whistles,":[134],"proposed":[136],"substantially":[138],"improves":[139],"several":[140],"baselines":[141],"performs":[143],"favorably":[144],"compared":[145],"state-of-the-art":[147],"on":[149],"five":[150],"crowd":[151],"datasets:":[153],"NWPU-Crowd,":[154],"ShanghaiTech":[155],"A":[156],"&":[157],"B,":[158],"UCF-QNRF,":[159],"JHU-Crowd++.":[161],"The":[162],"source":[163],"code":[164],"trained":[166],"models":[167],"released":[169],"<uri":[171],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[172],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/streamer-AP/PML_Loss.git</uri>":[173],".":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}