{"id":"https://openalex.org/W4285600988","doi":"https://doi.org/10.24963/ijcai.2022/130","title":"Learning Target-aware Representation for Visual Tracking via Informative Interactions","display_name":"Learning Target-aware Representation for Visual Tracking via Informative Interactions","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4285600988","doi":"https://doi.org/10.24963/ijcai.2022/130"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/130","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/130","pdf_url":"https://www.ijcai.org/proceedings/2022/0130.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2022/0130.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115444828","display_name":"Mingzhe Guo","orcid":"https://orcid.org/0000-0001-6399-9753"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingzhe Guo","raw_affiliation_strings":["Beijing Jiaotong University","Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410132","display_name":"Zhipeng Zhang","orcid":"https://orcid.org/0000-0003-0479-332X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Zhang","raw_affiliation_strings":["Chinese Academy of Sciences","National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047220188","display_name":"Heng Fan","orcid":"https://orcid.org/0000-0002-7033-3690"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heng Fan","raw_affiliation_strings":["University of North Texas","Department of Computer Science and Engineering, University of North Texas, Denton, TX USA"],"affiliations":[{"raw_affiliation_string":"University of North Texas","institution_ids":["https://openalex.org/I123534392"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, Denton, TX USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069749738","display_name":"Liping Jing","orcid":"https://orcid.org/0000-0001-7578-3407"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liping Jing","raw_affiliation_strings":["Beijing Jiaotong University","Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054177342","display_name":"Yilin Lyu","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilin Lyu","raw_affiliation_strings":["Beijing Jiaotong University","Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109346446","display_name":"Bing Li","orcid":"https://orcid.org/0000-0002-5888-6735"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Li","raw_affiliation_strings":["National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114549594","display_name":"Weiming Hu","orcid":"https://orcid.org/0000-0001-9237-8825"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Hu","raw_affiliation_strings":["Institute of Automation\uff0cChinese Academy of Sciences","National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation\uff0cChinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5115444828"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":3.5215,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":{"value":0.94777549,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"927","last_page":"934"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9977999925613403,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9955999851226807,"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":0.7746058702468872},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.7103146314620972},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5753352046012878},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.544006884098053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.537701427936554},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5081174373626709},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4942350685596466},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4938991665840149},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47854289412498474},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46720239520072937},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4116475582122803},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3256843090057373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09316542744636536},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08897989988327026},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07876598834991455}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7746058702468872},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.7103146314620972},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5753352046012878},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.544006884098053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.537701427936554},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5081174373626709},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4942350685596466},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4938991665840149},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47854289412498474},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46720239520072937},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4116475582122803},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3256843090057373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09316542744636536},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08897989988327026},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07876598834991455},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2022/130","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/130","pdf_url":"https://www.ijcai.org/proceedings/2022/0130.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/130","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/130","pdf_url":"https://www.ijcai.org/proceedings/2022/0130.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1614471940","display_name":null,"funder_award_id":"2020AAA0","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2326706895","display_name":null,"funder_award_id":"2020AAA0106800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4118857521","display_name":null,"funder_award_id":"62176020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6526070940","display_name":null,"funder_award_id":"Z180006","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8582926941","display_name":null,"funder_award_id":"Z180006","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"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285600988.pdf","grobid_xml":"https://content.openalex.org/works/W4285600988.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W1984914017","https://openalex.org/W2118097920","https://openalex.org/W2126302311","https://openalex.org/W2154889144","https://openalex.org/W2158592639","https://openalex.org/W2470394683","https://openalex.org/W2518876086","https://openalex.org/W2557641257","https://openalex.org/W2605173812","https://openalex.org/W2794744029","https://openalex.org/W2799058067","https://openalex.org/W2891033863","https://openalex.org/W2898200825","https://openalex.org/W2949846184","https://openalex.org/W2963534981","https://openalex.org/W2964423614","https://openalex.org/W2966759264","https://openalex.org/W2987460522","https://openalex.org/W3001584168","https://openalex.org/W3035211844","https://openalex.org/W3035511673","https://openalex.org/W3094502228","https://openalex.org/W3096609285","https://openalex.org/W3107331169","https://openalex.org/W3108519869","https://openalex.org/W3115390238","https://openalex.org/W3138516171","https://openalex.org/W3165150763","https://openalex.org/W3167536469","https://openalex.org/W3181069167","https://openalex.org/W3204554907","https://openalex.org/W4214893857","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2068608913","https://openalex.org/W3124914020","https://openalex.org/W2141033859","https://openalex.org/W2156434174","https://openalex.org/W2071701083","https://openalex.org/W2383687187","https://openalex.org/W2081517010","https://openalex.org/W2121496884","https://openalex.org/W2387910809","https://openalex.org/W4309346246"],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,111],"novel":[3],"backbone":[4,26,42,103,126,153],"architecture":[5],"to":[6,40,68,121,129,151],"improve":[7],"target-perception":[8,131],"ability":[9],"of":[10,63,85,108,124,132,178,187],"feature":[11,21,83,134],"representation":[12,61,135],"for":[13,28,159],"tracking.":[14],"Having":[15],"observed":[16],"de":[17],"facto":[18],"frameworks":[19],"perform":[20],"matching":[22,38,51],"simply":[23],"using":[24],"the":[25,37,41,45,50,56,60,69,73,82,93,101,118,125,168,172],"outputs":[27],"target":[29,57,119],"localization,":[30],"there":[31],"is":[32,66,110],"no":[33],"direct":[34],"feedback":[35],"from":[36],"module":[39,52,143],"network,":[43,127],"especially":[44],"shallow":[46,78],"layers.":[47,87],"Concretely,":[48],"only":[49],"can":[53],"directly":[54],"access":[55],"information,":[58],"while":[59],"learning":[62],"candidate":[64,133],"frame":[65],"blind":[67],"reference":[70],"target.":[71],"Therefore,":[72],"accumulated":[74],"target-irrelevant":[75],"interference":[76],"in":[77],"stages":[79,123],"may":[80],"degrade":[81],"quality":[84],"deeper":[86],"In":[88,166],"this":[89],"paper,":[90],"we":[91],"approach":[92],"problem":[94],"by":[95],"conducting":[96],"multiple":[97,164],"branch-wise":[98],"interactions":[99],"inside":[100],"Siamese-like":[102],"networks":[104],"(InBN).":[105],"The":[106,140,182],"core":[107],"InBN":[109,145],"general":[112,148],"interaction":[113],"modeler":[114],"(GIM)":[115],"that":[116],"injects":[117],"information":[120],"different":[122,152],"leading":[128],"better":[130],"with":[136,174,195],"negligible":[137],"computation":[138],"cost.":[139],"proposed":[141],"GIM":[142],"and":[144,149,157],"mechanism":[146],"are":[147,192],"applicable":[150],"types":[154],"including":[155],"CNN":[156,169],"Transformer":[158,183],"improvements,":[160],"as":[161],"evidenced":[162],"on":[163,180,189,193],"benchmarks.":[165],"particular,":[167],"version":[170,184],"improves":[171],"baseline":[173],"3.2/6.9":[175],"absolute":[176],"gains":[177],"SUC":[179,186],"LaSOT/TNL2K.":[181],"obtains":[185],"65.7/52.0":[188],"LaSOT/TNL2K,":[190],"which":[191],"par":[194],"recent":[196],"SOTAs.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":3}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}