{"id":"https://openalex.org/W3124616064","doi":"https://doi.org/10.1109/tip.2021.3051471","title":"Learning Diverse Models for End-to-End Ensemble Tracking","display_name":"Learning Diverse Models for End-to-End Ensemble Tracking","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3124616064","doi":"https://doi.org/10.1109/tip.2021.3051471","mag":"3124616064","pmid":"https://pubmed.ncbi.nlm.nih.gov/33471758"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2021.3051471","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3051471","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100387149","display_name":"Ning Wang","orcid":"https://orcid.org/0000-0002-4937-6784"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Wang","raw_affiliation_strings":["CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-4937-6784","affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046805800","display_name":"Wengang Zhou","orcid":"https://orcid.org/0000-0003-1690-9836"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wengang Zhou","raw_affiliation_strings":["CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-1690-9836","affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078141810","display_name":"Houqiang Li","orcid":"https://orcid.org/0000-0003-2188-3028"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houqiang Li","raw_affiliation_strings":["CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-2188-3028","affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.5653,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66155839,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"30","issue":null,"first_page":"2220","last_page":"2231"},"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":0.9876999855041504,"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/T11448","display_name":"Face recognition and analysis","score":0.9757999777793884,"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":0.7455751895904541},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6768268346786499},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6173001527786255},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5583778023719788},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.555040717124939},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.45308154821395874},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4244520664215088},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4194779396057129},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37709367275238037},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11637899279594421}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7455751895904541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6768268346786499},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6173001527786255},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5583778023719788},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.555040717124939},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.45308154821395874},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4244520664215088},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4194779396057129},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37709367275238037},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11637899279594421}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2021.3051471","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3051471","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:33471758","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33471758","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2262853887","display_name":null,"funder_award_id":"61836011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4052041763","display_name":null,"funder_award_id":"2018497","funder_id":"https://openalex.org/F4320322847","funder_display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences"},{"id":"https://openalex.org/G6191007303","display_name":null,"funder_award_id":"2018497","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G6697701469","display_name":null,"funder_award_id":"61822208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6846722749","display_name":null,"funder_award_id":"61836006","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/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320322847","display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences","ror":"https://ror.org/031141b54"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":80,"referenced_works":["https://openalex.org/W170496991","https://openalex.org/W182940129","https://openalex.org/W1522301498","https://openalex.org/W1857884451","https://openalex.org/W1861492603","https://openalex.org/W1955720507","https://openalex.org/W1964846093","https://openalex.org/W1995903777","https://openalex.org/W1997121481","https://openalex.org/W2102304169","https://openalex.org/W2154889144","https://openalex.org/W2158592639","https://openalex.org/W2194775991","https://openalex.org/W2214352687","https://openalex.org/W2408241409","https://openalex.org/W2421627342","https://openalex.org/W2470394683","https://openalex.org/W2470456807","https://openalex.org/W2518013266","https://openalex.org/W2518876086","https://openalex.org/W2557641257","https://openalex.org/W2599547527","https://openalex.org/W2605173812","https://openalex.org/W2610871254","https://openalex.org/W2681067697","https://openalex.org/W2737572441","https://openalex.org/W2740685955","https://openalex.org/W2742165450","https://openalex.org/W2776035257","https://openalex.org/W2794744029","https://openalex.org/W2797812763","https://openalex.org/W2798842862","https://openalex.org/W2799058067","https://openalex.org/W2886910176","https://openalex.org/W2888456413","https://openalex.org/W2891033863","https://openalex.org/W2894176037","https://openalex.org/W2894682667","https://openalex.org/W2895588569","https://openalex.org/W2897666265","https://openalex.org/W2898200825","https://openalex.org/W2937749627","https://openalex.org/W2954137266","https://openalex.org/W2955747520","https://openalex.org/W2955983623","https://openalex.org/W2962684187","https://openalex.org/W2962824803","https://openalex.org/W2962843811","https://openalex.org/W2962864296","https://openalex.org/W2962972233","https://openalex.org/W2963030525","https://openalex.org/W2963074722","https://openalex.org/W2963103976","https://openalex.org/W2963227409","https://openalex.org/W2963471260","https://openalex.org/W2963534981","https://openalex.org/W2963854930","https://openalex.org/W2964069521","https://openalex.org/W2964111344","https://openalex.org/W2964121744","https://openalex.org/W2964198573","https://openalex.org/W2964242925","https://openalex.org/W2964253307","https://openalex.org/W2964423614","https://openalex.org/W2966759264","https://openalex.org/W2987460522","https://openalex.org/W2997599718","https://openalex.org/W2998027361","https://openalex.org/W3001584168","https://openalex.org/W4293568472","https://openalex.org/W6606968713","https://openalex.org/W6607635097","https://openalex.org/W6631190155","https://openalex.org/W6639102338","https://openalex.org/W6641058392","https://openalex.org/W6685802191","https://openalex.org/W6726293469","https://openalex.org/W6754932287","https://openalex.org/W6755863804","https://openalex.org/W6772012192"],"related_works":["https://openalex.org/W2166802793","https://openalex.org/W2787993192","https://openalex.org/W1560144479","https://openalex.org/W1981324031","https://openalex.org/W2158269427","https://openalex.org/W2275805942","https://openalex.org/W4381280689","https://openalex.org/W3033859939","https://openalex.org/W2847365777","https://openalex.org/W1605318399"],"abstract_inverted_index":{"In":[0,18],"visual":[1],"tracking,":[2],"how":[3],"to":[4,28],"effectively":[5],"model":[6,95],"the":[7,58,65,72,79,87,94,114,119,137],"target":[8],"appearance":[9],"using":[10],"limited":[11],"prior":[12],"information":[13],"remains":[14],"an":[15,23,62],"open":[16],"problem.":[17],"this":[19],"paper,":[20],"we":[21,92],"leverage":[22],"ensemble":[24,38,75],"of":[25,74,89,140],"diverse":[26],"models":[27,69,84,143],"learn":[29],"manifold":[30],"representations":[31],"for":[32,45,53],"robust":[33],"object":[34],"tracking.":[35],"The":[36,147],"proposed":[37,148],"framework":[39,128],"includes":[40],"a":[41,111,133],"shared":[42,59],"backbone":[43],"network":[44],"efficient":[46],"feature":[47],"extraction":[48],"and":[49,97,144],"multiple":[50,83,141],"head":[51,68],"networks":[52],"independent":[54],"predictions.":[55],"Trained":[56],"by":[57,118],"data":[60],"within":[61],"identical":[63],"structure,":[64],"mutually":[66],"correlated":[67],"heavily":[70],"hinder":[71],"potential":[73],"learning.":[76],"To":[77],"shrink":[78],"representational":[80],"overlaps":[81],"among":[82],"while":[85,157],"encouraging":[86],"diversity":[88,96,99],"individual":[90],"predictions,":[91],"propose":[93],"response":[98],"regularization":[100],"terms":[101],"during":[102],"training.":[103],"By":[104],"fusing":[105],"these":[106],"distinctive":[107],"prediction":[108],"results":[109,152],"via":[110],"fusion":[112,145],"module,":[113],"tracking":[115],"variance":[116],"caused":[117],"distractor":[120],"objects":[121],"can":[122],"be":[123],"largely":[124],"restrained.":[125],"Our":[126],"whole":[127],"is":[129],"end-to-end":[130],"trained":[131],"in":[132,159],"data-driven":[134],"manner,":[135],"avoiding":[136],"heuristic":[138],"designs":[139],"base":[142],"strategies.":[146],"method":[149],"achieves":[150],"state-of-the-art":[151],"on":[153],"seven":[154],"challenging":[155],"benchmarks":[156],"operating":[158],"real-time.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
