{"id":"https://openalex.org/W2919735823","doi":"https://doi.org/10.1145/3297156.3297259","title":"Multi-feature fusion Siamese Network for Real-Time Object Tracking","display_name":"Multi-feature fusion Siamese Network for Real-Time Object Tracking","publication_year":2018,"publication_date":"2018-12-08","ids":{"openalex":"https://openalex.org/W2919735823","doi":"https://doi.org/10.1145/3297156.3297259","mag":"2919735823"},"language":"en","primary_location":{"id":"doi:10.1145/3297156.3297259","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297156.3297259","pdf_url":null,"source":{"id":"https://openalex.org/S4306523626","display_name":"Proceedings of the 2018 2nd International Conference on Computer Science and 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 2018 2nd International Conference on Computer Science and Artificial Intelligence","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/A5100747270","display_name":"Lijun Zhou","orcid":"https://orcid.org/0009-0003-6079-7349"},"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"]},{"id":"https://openalex.org/I4210128284","display_name":"Institute of Optics and Electronics, Chinese Academy of Sciences","ror":"https://ror.org/02bn68w95","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128284"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lijun Zhou","raw_affiliation_strings":["Institute of Optics and Electronics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute of Optics and Electronics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Chengdu, China","institution_ids":["https://openalex.org/I4210128284","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100623853","display_name":"Hongyun Li","orcid":"https://orcid.org/0000-0003-3332-3132"},"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"]},{"id":"https://openalex.org/I4210128284","display_name":"Institute of Optics and Electronics, Chinese Academy of Sciences","ror":"https://ror.org/02bn68w95","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128284"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyun Li","raw_affiliation_strings":["Institute of Optics and Electronics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute of Optics and Electronics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Chengdu, China","institution_ids":["https://openalex.org/I4210128284","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109487064","display_name":"Jianlin Zhang","orcid":null},"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"]},{"id":"https://openalex.org/I4210128284","display_name":"Institute of Optics and Electronics, Chinese Academy of Sciences","ror":"https://ror.org/02bn68w95","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128284"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianlin Zhang","raw_affiliation_strings":["Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, China","institution_ids":["https://openalex.org/I4210128284","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100747270"],"corresponding_institution_ids":["https://openalex.org/I4210128284","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24025974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"478","last_page":"481"},"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":0.9908000230789185,"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/benchmark","display_name":"Benchmark (surveying)","score":0.7883796095848083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7751895785331726},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6557714343070984},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.6283025145530701},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6271964907646179},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5831613540649414},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5418669581413269},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4923466444015503},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4825974702835083},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4342527687549591},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41151565313339233}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7883796095848083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7751895785331726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6557714343070984},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.6283025145530701},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6271964907646179},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5831613540649414},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5418669581413269},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4923466444015503},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4825974702835083},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4342527687549591},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41151565313339233},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3297156.3297259","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297156.3297259","pdf_url":null,"source":{"id":"https://openalex.org/S4306523626","display_name":"Proceedings of the 2018 2nd International Conference on Computer Science and 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 2018 2nd International Conference on Computer Science and Artificial Intelligence","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":23,"referenced_works":["https://openalex.org/W182940129","https://openalex.org/W1497265063","https://openalex.org/W1854404533","https://openalex.org/W1857884451","https://openalex.org/W1963882359","https://openalex.org/W1997121481","https://openalex.org/W2069332137","https://openalex.org/W2089961441","https://openalex.org/W2118097920","https://openalex.org/W2124211486","https://openalex.org/W2158592639","https://openalex.org/W2214352687","https://openalex.org/W2244956674","https://openalex.org/W2343187456","https://openalex.org/W2470394683","https://openalex.org/W2470456807","https://openalex.org/W2473868734","https://openalex.org/W2518013266","https://openalex.org/W2605381261","https://openalex.org/W2962824803","https://openalex.org/W2963446712","https://openalex.org/W2964111344","https://openalex.org/W4249142012"],"related_works":["https://openalex.org/W2951187577","https://openalex.org/W4285271403","https://openalex.org/W2542007731","https://openalex.org/W2968379562","https://openalex.org/W2091015105","https://openalex.org/W4388689193","https://openalex.org/W2110899030","https://openalex.org/W29633852","https://openalex.org/W2985362983","https://openalex.org/W4327670844"],"abstract_inverted_index":{"In":[0,42],"the":[1,5,8,20,23,26,38,40,46,67,87,94,109,123,129],"multilayer":[2],"neural":[3],"network,":[4],"features":[6,24,33,50,69,72],"of":[7,12,25,30,48,101,111],"low-level":[9,52,68],"layers":[10,28],"are":[11,29,35,73],"high":[13],"resolution,":[14],"which":[15,34],"is":[16,105,116],"suitable":[17,36],"for":[18,37,86,93],"positioning":[19],"object,":[21],"while":[22],"high-level":[27,49,71],"rich":[31],"semantics":[32],"classifying":[39],"object.":[41],"order":[43],"to":[44,118,133],"utilize":[45],"advantage":[47],"and":[51,70,121],"features,":[53],"we":[54],"introduce":[55],"a":[56],"densely":[57],"connected":[58],"network":[59,89,104],"called":[60],"DSiamFc(Densely":[61],"Connected":[62],"Siamese":[63],"Networks).":[64],"Not":[65],"only":[66],"fully":[74],"integrated,":[75],"but":[76],"also":[77],"this":[78],"connection":[79],"method":[80],"can":[81],"provide":[82],"better":[83],"parameter":[84],"adjustment":[85],"whole":[88],"during":[90],"off-line":[91],"training":[92],"end-to-end":[95],"object":[96,137],"tracking":[97,138],"network.":[98],"The":[99],"effectiveness":[100],"our":[102,126],"proposed":[103],"demonstrated":[106],"by":[107],"analyzing":[108],"backpropagation":[110],"gradient":[112],"flow.":[113],"Our":[114],"algorithm":[115,127],"able":[117],"achieve":[119],"real-time,":[120],"in":[122],"OTB-2013/50/100":[124],"benchmark,":[125],"has":[128],"best":[130],"performance":[131],"compared":[132],"other":[134],"state-of-the-art":[135],"real-time":[136],"algorithms.":[139]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
