{"id":"https://openalex.org/W4293704739","doi":"https://doi.org/10.1109/tcds.2022.3202802","title":"Deep Decoupling Classification and Regression for Visual Tracking","display_name":"Deep Decoupling Classification and Regression for Visual Tracking","publication_year":2022,"publication_date":"2022-08-30","ids":{"openalex":"https://openalex.org/W4293704739","doi":"https://doi.org/10.1109/tcds.2022.3202802"},"language":"en","primary_location":{"id":"doi:10.1109/tcds.2022.3202802","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcds.2022.3202802","pdf_url":null,"source":{"id":"https://openalex.org/S2488537894","display_name":"IEEE Transactions on Cognitive and Developmental Systems","issn_l":"2379-8920","issn":["2379-8920","2379-8939"],"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 Cognitive and Developmental Systems","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/A5071370650","display_name":"Guang Han","orcid":"https://orcid.org/0000-0003-4812-9180"},"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":"Guang Han","raw_affiliation_strings":["Engineering Research Center of Wideband Wireless Communication Technology, Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-4812-9180","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Wideband Wireless Communication Technology, Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035918739","display_name":"Ruiyu Yang","orcid":null},"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":"Ruiyu Yang","raw_affiliation_strings":["Engineering Research Center of Wideband Wireless Communication Technology, Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Engineering Research Center of Wideband Wireless Communication Technology, Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081892355","display_name":"Hua Gao","orcid":"https://orcid.org/0000-0003-1015-5367"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Gao","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008386708","display_name":"Sam Kwong","orcid":"https://orcid.org/0000-0001-7484-7261"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sam Kwong","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7484-7261","affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071370650"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.3061,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54664036,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"15","issue":"3","first_page":"1239","last_page":"1251"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9897000193595886,"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/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.8775960206985474},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8646436929702759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6809762120246887},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5999121069908142},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5525646805763245},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5478824973106384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45506545901298523},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.445144385099411},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41821372509002686},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.41614633798599243},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3275489807128906},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.2544662356376648}],"concepts":[{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.8775960206985474},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8646436929702759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6809762120246887},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5999121069908142},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5525646805763245},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5478824973106384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45506545901298523},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.445144385099411},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41821372509002686},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.41614633798599243},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3275489807128906},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.2544662356376648},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcds.2022.3202802","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcds.2022.3202802","pdf_url":null,"source":{"id":"https://openalex.org/S2488537894","display_name":"IEEE Transactions on Cognitive and Developmental Systems","issn_l":"2379-8920","issn":["2379-8920","2379-8939"],"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 Cognitive and Developmental Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3565108176","display_name":null,"funder_award_id":"61302156","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5921356299","display_name":null,"funder_award_id":"61871445","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/W639708223","https://openalex.org/W1861492603","https://openalex.org/W1995903777","https://openalex.org/W2117539524","https://openalex.org/W2155996542","https://openalex.org/W2194775991","https://openalex.org/W2326683933","https://openalex.org/W2408241409","https://openalex.org/W2470394683","https://openalex.org/W2518876086","https://openalex.org/W2610871254","https://openalex.org/W2625998969","https://openalex.org/W2794744029","https://openalex.org/W2797812763","https://openalex.org/W2799058067","https://openalex.org/W2886910176","https://openalex.org/W2891033863","https://openalex.org/W2898200825","https://openalex.org/W2917101430","https://openalex.org/W2917610807","https://openalex.org/W2937749627","https://openalex.org/W2944255943","https://openalex.org/W2962766617","https://openalex.org/W2963227409","https://openalex.org/W2963534981","https://openalex.org/W2963854930","https://openalex.org/W2964198573","https://openalex.org/W2981352030","https://openalex.org/W2998434318","https://openalex.org/W3001584168","https://openalex.org/W3035211844","https://openalex.org/W3035453691","https://openalex.org/W3035460038","https://openalex.org/W3035511673","https://openalex.org/W3096609285","https://openalex.org/W3101488456","https://openalex.org/W3103005696","https://openalex.org/W3108519869","https://openalex.org/W3167536469","https://openalex.org/W3167762749","https://openalex.org/W3168649818","https://openalex.org/W3168663926","https://openalex.org/W3174225630","https://openalex.org/W3204554907","https://openalex.org/W3214586131","https://openalex.org/W4214759957","https://openalex.org/W4221049076","https://openalex.org/W4312805142","https://openalex.org/W6631943919","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6757817989","https://openalex.org/W6770506093","https://openalex.org/W6787985011","https://openalex.org/W6788023325"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"Classification":[0],"and":[1,49,90,153],"regression":[2,50],"are":[3,61,95],"two":[4,27,56,68,78],"tasks":[5],"that":[6,138],"most":[7,14],"Siamese-based":[8],"trackers":[9,18],"need":[10],"to":[11,24,34,45,63,70],"handle.":[12],"However,":[13],"of":[15,29,86,116,128,151],"the":[16,52,65,72,77,83,98,105,114,125,132,149,167],"existing":[17],"only":[19],"learn":[20],"one":[21],"feature":[22,57],"embedding":[23],"handle":[25],"these":[26],"types":[28],"task,":[30],"making":[31],"it":[32],"difficult":[33],"optimize":[35],"both":[36],"simultaneously.":[37],"To":[38],"solve":[39],"this":[40,42,145],"problem,":[41],"article":[43,146],"tries":[44],"deeply":[46],"decouple":[47],"classification":[48,152],"in":[51,131,144],"model":[53,66],"structure.":[54],"Specifically,":[55],"extraction":[58],"backbone":[59],"networks":[60],"used":[62],"divide":[64],"into":[67],"branches":[69,94],"extract":[71],"heterogeneous":[73],"features":[74],"suitable":[75],"for":[76],"tasks,":[79],"respectively.":[80],"Inspired":[81],"by":[82,97,122],"core":[84],"idea":[85],"transformer,":[87],"information":[88,107,118],"interaction":[89,119],"fusion":[91],"between":[92,109],"multiple":[93,110],"achieved":[96],"cross-attention":[99],"mechanism,":[100],"which":[101],"can":[102],"fully":[103],"exploit":[104],"deep":[106],"dependence":[108],"branches.":[111],"In":[112],"addition,":[113],"concept":[115],"channel-level":[117],"is":[120],"proposed":[121],"innovatively":[123],"changing":[124],"generation":[126],"mode":[127],"vector":[129],"groups":[130],"attention":[133],"module.":[134],"The":[135],"experiments":[136],"show":[137],"double":[139],"Siamese":[140],"tracker":[141],"(DST)":[142],"designed":[143],"greatly":[147],"improves":[148],"accuracy":[150],"regression.":[154],"DST":[155],"runs":[156],"at":[157],"60":[158],"frames":[159],"per":[160],"second":[161],"(FPS)":[162],"on":[163],"GPU,":[164],"far":[165],"above":[166],"real-time":[168],"requirement.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}