{"id":"https://openalex.org/W3001222093","doi":"https://doi.org/10.1109/vcip47243.2019.8965683","title":"Efficient Dual Attention Module for Real-Time Visual Tracking","display_name":"Efficient Dual Attention Module for Real-Time Visual Tracking","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3001222093","doi":"https://doi.org/10.1109/vcip47243.2019.8965683","mag":"3001222093"},"language":"en","primary_location":{"id":"doi:10.1109/vcip47243.2019.8965683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip47243.2019.8965683","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5072520602","display_name":"Yingsen Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingsen Zeng","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102864522","display_name":"Xiaoqiang Guo","orcid":"https://orcid.org/0000-0003-2355-0569"},"institutions":[{"id":"https://openalex.org/I4210111085","display_name":"Academy of Broadcasting Science","ror":"https://ror.org/01z4nez64","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210111085"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqiang Guo","raw_affiliation_strings":["Academy of Broadcasting Science,Beijing,China","Academy of Broadcasting Science, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Broadcasting Science,Beijing,China","institution_ids":["https://openalex.org/I4210111085"]},{"raw_affiliation_string":"Academy of Broadcasting Science, Beijing, China","institution_ids":["https://openalex.org/I4210111085"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102934586","display_name":"Haiying Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiying Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035202066","display_name":"Mingjin Geng","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjin Geng","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113490231","display_name":"Ting Lu","orcid":"https://orcid.org/0000-0002-0898-2833"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Lu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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":0.9897000193595886,"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"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9866999983787537,"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/discriminative-model","display_name":"Discriminative model","score":0.8122308254241943},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7491534948348999},{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.6881517171859741},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6707344055175781},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6701653003692627},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5824748277664185},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5750574469566345},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5438897609710693},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.530849814414978},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.5066078901290894},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4772588908672333},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4633373022079468},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.4557192027568817},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4429139196872711},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4291422367095947},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32980412244796753},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1411667764186859},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11788082122802734}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8122308254241943},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7491534948348999},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.6881517171859741},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6707344055175781},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6701653003692627},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5824748277664185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5750574469566345},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5438897609710693},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.530849814414978},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.5066078901290894},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4772588908672333},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4633373022079468},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.4557192027568817},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4429139196872711},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4291422367095947},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32980412244796753},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1411667764186859},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11788082122802734},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip47243.2019.8965683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip47243.2019.8965683","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1857884451","https://openalex.org/W2089961441","https://openalex.org/W2117539524","https://openalex.org/W2470394683","https://openalex.org/W2557641257","https://openalex.org/W2599547527","https://openalex.org/W2752782242","https://openalex.org/W2797812763","https://openalex.org/W2799058067","https://openalex.org/W2884585870","https://openalex.org/W2888456413","https://openalex.org/W2955058313","https://openalex.org/W2962824803","https://openalex.org/W2963091558","https://openalex.org/W2963420686","https://openalex.org/W2963854930","https://openalex.org/W2964099559","https://openalex.org/W2982220924","https://openalex.org/W6720898849","https://openalex.org/W6753412334","https://openalex.org/W6754852571"],"related_works":["https://openalex.org/W4384788979","https://openalex.org/W2511178891","https://openalex.org/W178060743","https://openalex.org/W2909390414","https://openalex.org/W2126676984","https://openalex.org/W2954509079","https://openalex.org/W2141888607","https://openalex.org/W2753886513","https://openalex.org/W2070920257","https://openalex.org/W1765993298"],"abstract_inverted_index":{"Attention":[0,48],"mechanisms":[1,40],"are":[2],"of":[3,12,21,109,121],"great":[4],"potential":[5],"to":[6,18,26,58,116],"enhance":[7],"discriminative":[8,117],"capacity":[9],"and":[10,55,63,70,95,98,118],"adaptability":[11],"Convolutional":[13],"Neural":[14],"Networks.":[15],"However,":[16],"due":[17],"speed":[19],"requirements":[20],"trackers,":[22],"it":[23],"is":[24,52,82],"inappropriate":[25],"introduce":[27],"attention":[28,39,60,91],"modules":[29],"that":[30,131],"need":[31],"high":[32],"computational-cost":[33],"into":[34],"tracking":[35,42,128],"algorithms.":[36],"To":[37],"employ":[38],"in":[41,61,102],"field,":[43],"we":[44,67,88],"propose":[45],"Efficient":[46],"Dual":[47],"Module":[49],"(EDAM)":[50],"which":[51,81],"a":[53,77,103,126],"lightweight":[54],"effective":[56],"module":[57],"extract":[59,89],"channel":[62,71],"spatial":[64,69],"dimensions.":[65],"Firstly,":[66],"aggregate":[68],"information":[72],"with":[73,134],"self-attention":[74],"mechanism":[75],"by":[76,92],"simplified":[78],"Non-local":[79],"Network,":[80],"called":[83],"Attention-wise":[84],"Global":[85],"Pooling.":[86],"Next,":[87],"dual":[90,110],"modeling":[93],"inter-channel":[94],"inter-position":[96],"relationships":[97],"finally":[99],"fuse":[100],"them":[101],"sequential":[104],"manner.":[105],"With":[106],"the":[107,112],"use":[108],"attention,":[111],"network":[113],"adaptively":[114],"attends":[115],"robust":[119],"features":[120],"targets.":[122],"Extensive":[123],"experiments":[124],"on":[125],"standard":[127],"benchmark":[129],"demonstrate":[130],"our":[132],"tracker":[133],"an":[135],"EDAM":[136],"embedded":[137],"achieves":[138],"favorable":[139],"performance":[140],"against":[141],"state-of-the-art":[142],"trackers":[143],"while":[144],"runs":[145],"at":[146],"real-time":[147],"speed.":[148]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
