{"id":"https://openalex.org/W4377971406","doi":"https://doi.org/10.1109/tmm.2023.3279670","title":"Similarity- and Quality-Guided Relation Learning for Joint Detection and Tracking","display_name":"Similarity- and Quality-Guided Relation Learning for Joint Detection and Tracking","publication_year":2023,"publication_date":"2023-05-24","ids":{"openalex":"https://openalex.org/W4377971406","doi":"https://doi.org/10.1109/tmm.2023.3279670"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2023.3279670","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tmm.2023.3279670","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","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/A5072751690","display_name":"Weitao Feng","orcid":"https://orcid.org/0000-0003-2517-9206"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Weitao Feng","raw_affiliation_strings":["School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028486493","display_name":"Lei Bai","orcid":"https://orcid.org/0000-0003-3378-7201"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Bai","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001649888","display_name":"Yongqiang Yao","orcid":"https://orcid.org/0009-0002-1941-9904"},"institutions":[{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727009"]},{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongqiang Yao","raw_affiliation_strings":["SenseTime Group Ltd., Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd., Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I4210128910","https://openalex.org/I4401727009"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032006890","display_name":"Weihao Gan","orcid":"https://orcid.org/0000-0002-4076-6452"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]},{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihao Gan","raw_affiliation_strings":["SenseTime Group Ltd., Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd., Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I4210128910","https://openalex.org/I4401727009"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101584040","display_name":"Wei Wu","orcid":"https://orcid.org/0000-0001-5757-4476"},"institutions":[{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727009"]},{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wu","raw_affiliation_strings":["SenseTime Group Ltd., Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd., Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I4210128910","https://openalex.org/I4401727009"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087818121","display_name":"Wanli Ouyang","orcid":"https://orcid.org/0000-0002-9163-2761"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wanli Ouyang","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5072751690"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":null,"apc_paid":null,"fwci":0.369,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58148536,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"26","issue":null,"first_page":"1267","last_page":"1280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9793999791145325,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9136000275611877,"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":0.8056020140647888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6709974408149719},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6610673666000366},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6335098743438721},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5638229250907898},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5177828073501587},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4968915283679962},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4848548173904419},{"id":"https://openalex.org/keywords/spatial-relation","display_name":"Spatial relation","score":0.47331368923187256},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.46443140506744385},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45439767837524414},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.44956350326538086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4380890130996704},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33339470624923706},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12064191699028015}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8056020140647888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6709974408149719},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6610673666000366},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6335098743438721},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5638229250907898},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5177828073501587},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4968915283679962},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4848548173904419},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.47331368923187256},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.46443140506744385},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45439767837524414},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.44956350326538086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4380890130996704},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33339470624923706},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12064191699028015},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2023.3279670","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tmm.2023.3279670","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6370828123","display_name":null,"funder_award_id":"DP200103223","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1521019969","https://openalex.org/W1531192956","https://openalex.org/W1861492603","https://openalex.org/W2117539524","https://openalex.org/W2291627510","https://openalex.org/W2518253596","https://openalex.org/W2534578893","https://openalex.org/W2739491435","https://openalex.org/W2793130599","https://openalex.org/W2798542761","https://openalex.org/W2806331055","https://openalex.org/W2883108970","https://openalex.org/W2886581236","https://openalex.org/W2890773826","https://openalex.org/W2895150009","https://openalex.org/W2897861496","https://openalex.org/W2898044248","https://openalex.org/W2902137659","https://openalex.org/W2920942303","https://openalex.org/W2940928832","https://openalex.org/W2962855257","https://openalex.org/W2963091558","https://openalex.org/W2963481014","https://openalex.org/W2964019074","https://openalex.org/W2964086649","https://openalex.org/W2964286567","https://openalex.org/W2967086232","https://openalex.org/W2981393651","https://openalex.org/W2981648413","https://openalex.org/W2983208726","https://openalex.org/W2990211277","https://openalex.org/W2990578161","https://openalex.org/W3004910693","https://openalex.org/W3010594275","https://openalex.org/W3012922853","https://openalex.org/W3034240185","https://openalex.org/W3034334609","https://openalex.org/W3034467781","https://openalex.org/W3035442500","https://openalex.org/W3035727180","https://openalex.org/W3041577240","https://openalex.org/W3084173793","https://openalex.org/W3095753995","https://openalex.org/W3096068180","https://openalex.org/W3106920598","https://openalex.org/W3157260713","https://openalex.org/W3164698655","https://openalex.org/W3165926952","https://openalex.org/W3167949052","https://openalex.org/W3175782503","https://openalex.org/W3176403636","https://openalex.org/W3184439416","https://openalex.org/W3207452968","https://openalex.org/W4206711703","https://openalex.org/W4214494320","https://openalex.org/W4214516362","https://openalex.org/W4225724731","https://openalex.org/W4288325606","https://openalex.org/W4295331127","https://openalex.org/W4383755718","https://openalex.org/W6620707391","https://openalex.org/W6696672603","https://openalex.org/W6739901393","https://openalex.org/W6750697433","https://openalex.org/W6764322716","https://openalex.org/W6775253321","https://openalex.org/W6779650541","https://openalex.org/W6798838024"],"related_works":["https://openalex.org/W4307322379","https://openalex.org/W2098801107","https://openalex.org/W2554403468","https://openalex.org/W2382607599","https://openalex.org/W2016461833","https://openalex.org/W2052253960","https://openalex.org/W2147802381","https://openalex.org/W2546942002","https://openalex.org/W3202305871","https://openalex.org/W2785535669"],"abstract_inverted_index":{"Joint":[0],"detection":[1,106,142],"and":[2,37,83,143,159,212,263],"tracking,":[3],"which":[4,65,116],"solves":[5],"two":[6],"fundamental":[7],"vision":[8],"challenges":[9],"in":[10,18,30,64,112,115,130,188,204,235],"a":[11,15,80,117,146,152,236],"unified":[12],"manner,":[13],"is":[14,79,109],"challenging":[16,249],"topic":[17],"computer":[19],"vision.":[20],"In":[21,74,202],"this":[22,128,131],"area,":[23],"the":[24,39,102,171,178,189,197,241,261],"proper":[25],"use":[26],"of":[27,41,105,119,184,199],"spatial-temporal":[28,49,55,137],"information":[29,50,139],"videos":[31],"can":[32],"help":[33],"reduce":[34],"local":[35],"defects":[36],"improve":[38],"quality":[40,213],"feature":[42,88,180,238],"representations.":[43,89],"Although":[44],"modeling":[45,76],"low-level":[46],"(usually":[47],"pixel-wise)":[48],"has":[51],"been":[52,71],"studied,":[53],"instance-level":[54,77,96,136],"correlations":[56],"(<italic":[57],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[58],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i.e.</i>,":[59],"relations":[60],"between":[61],"semantic":[62,138],"regions":[63],"instances":[66,187],"have":[67,69,92],"occurred)":[68],"not":[70,110],"fully":[72],"exploited.":[73],"comparison,":[75],"correlation":[78],"more":[81,258],"flexible":[82],"reasonable":[84],"way":[85],"to":[86,126,176,210],"enhance":[87],"However,":[90],"we":[91,133,164,224],"found":[93],"that":[94,99,216,254],"conventional":[95],"relation":[97,148,154,168,232],"learning":[98,149,155],"works":[100],"for":[101,140,229,240],"separate":[103],"tasks":[104,114],"or":[107],"tracking":[108,144,251],"effective":[111,259],"joint":[113,141,147],"variety":[118],"scenarios":[120],"may":[121],"be":[122,221],"presented.":[123],"To":[124],"try":[125],"resolve":[127],"problem,":[129],"study,":[132],"effectively":[134],"exploited":[135],"via":[145],"pipeline":[150],"with":[151,268],"novel":[153],"mechanism":[156],"called":[157],"Similarity-":[158],"Quality-Guided":[160],"Attention":[161],"(SQGA).":[162],"Specifically,":[163],"added":[165,225],"task-specific":[166,226],"SQGA":[167,231],"modules":[169],"before":[170],"corresponding":[172,242],"task":[173],"prediction":[174],"heads":[175],"refine":[177],"instance":[179],"representation":[181],"using":[182],"features":[183,193],"other":[185],"reference":[186],"neighboring":[190],"frames;":[191],"these":[192],"are":[194],"aggregated":[195],"on":[196,247],"basis":[198],"relational":[200,206],"affinities.":[201],"particular,":[203],"SQGA,":[205],"affinities":[207],"were":[208],"factorized":[209],"similarity":[211],"terms":[214],"so":[215],"fine-grained":[217],"supervision":[218],"rules":[219],"could":[220],"applied.":[222],"Then":[223],"attention":[227],"losses":[228],"each":[230],"module,":[233],"resulting":[234],"better":[237],"aggregation":[239],"task.":[243],"Quantitative":[244],"experiments":[245],"based":[246],"several":[248],"multi-object":[250],"benchmarks":[252],"showed":[253],"our":[255],"approach":[256],"was":[257],"than":[260],"baselines":[262],"provided":[264],"competitive":[265],"results":[266],"compared":[267],"recent":[269],"state-of-the-art":[270],"methods.":[271]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
