{"id":"https://openalex.org/W3183342068","doi":"https://doi.org/10.1145/3459212.3459215","title":"Meta-Learning based Siamese Network with Channel-wise Self-attention for Visual Tracking","display_name":"Meta-Learning based Siamese Network with Channel-wise Self-attention for Visual Tracking","publication_year":2021,"publication_date":"2021-03-19","ids":{"openalex":"https://openalex.org/W3183342068","doi":"https://doi.org/10.1145/3459212.3459215","mag":"3183342068"},"language":"en","primary_location":{"id":"doi:10.1145/3459212.3459215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459212.3459215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 3rd International Conference on Image, Video and Signal Processing","raw_type":"proceedings-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/A5100431257","display_name":"Rui Wang","orcid":"https://orcid.org/0009-0003-8935-3119"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Wang","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023868028","display_name":"Bin Kang","orcid":"https://orcid.org/0000-0002-6054-7556"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Kang","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033247734","display_name":"Wei\u2010Ping Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wei-Ping Zhu","raw_affiliation_strings":["Concordia University and Nanjing University of Posts and Telecommunications, Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University and Nanjing University of Posts and Telecommunications, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100431257"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.0961,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.37841503,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"14","last_page":"19"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9894000291824341,"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":0.8110359907150269},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.711417019367218},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6858760714530945},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.666565477848053},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.624481201171875},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5368967652320862},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5199057459831238},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.49238502979278564},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.47537413239479065},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4573293626308441},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45049819350242615},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4433271586894989},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4291281998157501},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33949756622314453},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.1804923117160797},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07365486025810242},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06827282905578613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8110359907150269},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.711417019367218},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6858760714530945},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.666565477848053},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.624481201171875},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5368967652320862},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5199057459831238},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.49238502979278564},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.47537413239479065},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4573293626308441},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45049819350242615},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4433271586894989},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4291281998157501},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33949756622314453},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.1804923117160797},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07365486025810242},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06827282905578613},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459212.3459215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459212.3459215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 3rd International Conference on Image, Video and Signal Processing","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/W1955741794","https://openalex.org/W1964846093","https://openalex.org/W2097117768","https://openalex.org/W2408241409","https://openalex.org/W2470394683","https://openalex.org/W2557641257","https://openalex.org/W2604763608","https://openalex.org/W2799058067","https://openalex.org/W2894176037","https://openalex.org/W2898200825","https://openalex.org/W2962824803","https://openalex.org/W2963227409","https://openalex.org/W2963311325","https://openalex.org/W2963420686","https://openalex.org/W2963499285","https://openalex.org/W2963943197","https://openalex.org/W2964111344","https://openalex.org/W2964423614","https://openalex.org/W3102624093"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2043093291","https://openalex.org/W2363545964"],"abstract_inverted_index":{"A":[0],"great":[1],"deal":[2],"of":[3,23,56,80,91,111],"attention":[4],"has":[5],"been":[6],"paid":[7],"to":[8,27,59,101],"Siamese":[9,17,47],"networks":[10],"in":[11,63,85,144,149],"visual":[12],"object":[13],"tracking.":[14],"However,":[15],"the":[16,21,31,54,81,86,92,108,112,117,134,138],"network":[18,48,113],"often":[19],"faces":[20],"problem":[22],"over-fitting":[24,118],"when":[25],"adapting":[26],"new":[28],"scenes,":[29],"where":[30],"training":[32],"samples":[33],"for":[34,69,77],"scene":[35,71],"adaptation":[36,72],"are":[37,98],"limited.":[38],"In":[39],"this":[40,61],"paper,":[41],"we":[42],"propose":[43],"a":[44],"meta-learning":[45,65,87,130],"based":[46,122,131],"with":[49],"channel-wise":[50],"self-attention":[51],"(CSA)":[52],"on":[53,123],"basis":[55],"SiamFC3s":[57,132,141],"architecture":[58],"overcome":[60],"limitation,":[62],"which":[64,104],"mechanism":[66],"is":[67,75],"adopted":[68],"efficient":[70],"and":[73,147],"CSA":[74,136],"used":[76],"better":[78],"representation":[79],"target":[82],"object.":[83],"Specifically,":[84],"phase,":[88],"only":[89,106],"part":[90],"neurons'":[93],"parameters,":[94],"called":[95],"hyper":[96],"parameters":[97],"updated,":[99],"leading":[100],"lightweight":[102],"adaptation,":[103],"not":[105],"reduces":[107],"computational":[109],"burden":[110],"but":[114],"also":[115],"overcomes":[116],"problem.":[119],"Experimental":[120],"results":[121],"benchmark":[124],"OTB-100":[125],"have":[126],"shown":[127],"that":[128],"our":[129],"incorporating":[133],"proposed":[135],"outperforms":[137],"baseline":[139],"method":[140],"by":[142],"3.4%":[143],"success":[145],"rate":[146],"5.6%":[148],"precision":[150],"rate.":[151]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}