{"id":"https://openalex.org/W2922332129","doi":"https://doi.org/10.1109/tip.2019.2904434","title":"SMART: Joint Sampling and Regression for Visual Tracking","display_name":"SMART: Joint Sampling and Regression for Visual Tracking","publication_year":2019,"publication_date":"2019-03-12","ids":{"openalex":"https://openalex.org/W2922332129","doi":"https://doi.org/10.1109/tip.2019.2904434","mag":"2922332129","pmid":"https://pubmed.ncbi.nlm.nih.gov/30872227"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2019.2904434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2904434","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/A5014526931","display_name":"Junyu Gao","orcid":"https://orcid.org/0000-0002-8105-5497"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyu Gao","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648981","display_name":"Tianzhu Zhang","orcid":"https://orcid.org/0000-0003-1856-9564"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianzhu Zhang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1856-9564","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Xu","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8343-9665","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.191,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.82729135,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"28","issue":"8","first_page":"3923","last_page":"3935"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9854000210762024,"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":0.9836000204086304,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7632066011428833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.627460241317749},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6152797341346741},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.572173535823822},{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.5300198197364807},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5168426632881165},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5082678198814392},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47991499304771423},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4505201578140259},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.41344892978668213},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4030241072177887},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3617902994155884},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.28306281566619873},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.22249367833137512},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1411457359790802},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11751729249954224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7632066011428833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.627460241317749},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6152797341346741},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.572173535823822},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.5300198197364807},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5168426632881165},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5082678198814392},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47991499304771423},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4505201578140259},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.41344892978668213},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4030241072177887},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3617902994155884},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28306281566619873},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.22249367833137512},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1411457359790802},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11751729249954224},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2019.2904434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2904434","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:30872227","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30872227","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":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1353530241","display_name":null,"funder_award_id":"U1705262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1873612269","display_name":null,"funder_award_id":"61720106006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3164155781","display_name":"\u590d\u6742\u573a\u666f\u4e0b\u975e\u5408\u4f5c\u76ee\u6807\u9c81\u68d2\u8bc6\u522b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61472379","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3901002356","display_name":null,"funder_award_id":"61572296","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4670264125","display_name":"\u5927\u6570\u636e\u73af\u5883\u4e0b\u590d\u6742\u591a\u5a92\u4f53\u5185\u5bb9\u5206\u6790\u3001\u63a8\u9001\u4e0e\u5c55\u793a","funder_award_id":"61432019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6431871145","display_name":null,"funder_award_id":"61721004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7208724564","display_name":null,"funder_award_id":"61532009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7514903982","display_name":"\u57fa\u4e8e\u9c81\u68d2\u8868\u89c2\u5efa\u6a21\u7684\u76ee\u6807\u8ddf\u8e2a\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61772244","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7899093858","display_name":null,"funder_award_id":"61751211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8201791774","display_name":null,"funder_award_id":"61728210","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8412576099","display_name":"\u57fa\u4e8e\u4e8c\u5143\u7a7a\u95f4\u534f\u540c\u7684\u793e\u4f1a\u70ed\u70b9\u4e8b\u4ef6\u5206\u6790\u7814\u7a76","funder_award_id":"61572498","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8568116287","display_name":null,"funder_award_id":"4172062","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":88,"referenced_works":["https://openalex.org/W182940129","https://openalex.org/W639708223","https://openalex.org/W1560733133","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1854404533","https://openalex.org/W1857884451","https://openalex.org/W1892578678","https://openalex.org/W1903029394","https://openalex.org/W1915599933","https://openalex.org/W1915785815","https://openalex.org/W1937954682","https://openalex.org/W1955514522","https://openalex.org/W1955741794","https://openalex.org/W1960880753","https://openalex.org/W1984914017","https://openalex.org/W1997121481","https://openalex.org/W2069332137","https://openalex.org/W2083616304","https://openalex.org/W2089961441","https://openalex.org/W2098854771","https://openalex.org/W2098941887","https://openalex.org/W2102674365","https://openalex.org/W2118097920","https://openalex.org/W2126302311","https://openalex.org/W2132103241","https://openalex.org/W2138621090","https://openalex.org/W2139047213","https://openalex.org/W2143331230","https://openalex.org/W2154889144","https://openalex.org/W2155893237","https://openalex.org/W2158592639","https://openalex.org/W2158917775","https://openalex.org/W2165797462","https://openalex.org/W2167089254","https://openalex.org/W2170865122","https://openalex.org/W2186330282","https://openalex.org/W2208572097","https://openalex.org/W2211629196","https://openalex.org/W2214352687","https://openalex.org/W2216125271","https://openalex.org/W2408241409","https://openalex.org/W2464915613","https://openalex.org/W2469175529","https://openalex.org/W2469582947","https://openalex.org/W2470394683","https://openalex.org/W2473868734","https://openalex.org/W2480631127","https://openalex.org/W2518013266","https://openalex.org/W2518876086","https://openalex.org/W2556108308","https://openalex.org/W2557641257","https://openalex.org/W2558899534","https://openalex.org/W2579238278","https://openalex.org/W2610871254","https://openalex.org/W2616960207","https://openalex.org/W2738318237","https://openalex.org/W2740685955","https://openalex.org/W2742165450","https://openalex.org/W2771877920","https://openalex.org/W2776035257","https://openalex.org/W2784375960","https://openalex.org/W2784746431","https://openalex.org/W2790441826","https://openalex.org/W2954137266","https://openalex.org/W2962778460","https://openalex.org/W2962824803","https://openalex.org/W2962989418","https://openalex.org/W2963037989","https://openalex.org/W2963249584","https://openalex.org/W2963685263","https://openalex.org/W2963791342","https://openalex.org/W2964099559","https://openalex.org/W2964111344","https://openalex.org/W2964253307","https://openalex.org/W3195149063","https://openalex.org/W6607635097","https://openalex.org/W6633795679","https://openalex.org/W6638992375","https://openalex.org/W6639204139","https://openalex.org/W6649598916","https://openalex.org/W6677907805","https://openalex.org/W6679027886","https://openalex.org/W6683636472","https://openalex.org/W6703518758","https://openalex.org/W6720898849","https://openalex.org/W6726293469","https://openalex.org/W6765254102"],"related_works":["https://openalex.org/W2803618243","https://openalex.org/W3020706491","https://openalex.org/W256589335","https://openalex.org/W2804764393","https://openalex.org/W4385454113","https://openalex.org/W4386114301","https://openalex.org/W4386158955","https://openalex.org/W4384788979","https://openalex.org/W2511178891","https://openalex.org/W2126676984"],"abstract_inverted_index":{"Most":[0],"existing":[1],"trackers":[2,151],"are":[3,62],"either":[4],"sampling-based":[5],"or":[6],"regression-based":[7],"methods.":[8],"Sampling-based":[9],"methods":[10,22,35,55,76],"estimate":[11],"the":[12,46,98,131],"target":[13,18,113,118,122],"state":[14],"by":[15,102],"sampling":[16,89],"many":[17],"candidates.":[19],"Although":[20],"these":[21,54],"achieve":[23],"significant":[24],"performance,":[25],"they":[26],"often":[27,36],"suffer":[28],"from":[29],"a":[30,38,87,103,125],"high":[31],"computational":[32],"burden.":[33],"Regression-based":[34],"learn":[37],"computationally":[39],"efficient":[40],"regression":[41,91,119],"function":[42],"to":[43,120,154],"directly":[44],"predict":[45,121],"geometric":[47],"distortion":[48],"between":[49],"frames.":[50],"However,":[51],"most":[52],"of":[53,69,75],"require":[56],"large-scale":[57],"external":[58],"training":[59],"videos":[60],"and":[61,78,90,116,138,157],"still":[63],"not":[64],"very":[65],"impressive":[66],"in":[67,82,124],"terms":[68],"accuracy.":[70],"To":[71],"make":[72],"both":[73,155],"types":[74],"enhance":[77],"complement":[79],"each":[80],"other,":[81],"this":[83],"paper,":[84],"we":[85],"propose":[86],"joint":[88],"scheme":[92],"for":[93],"visual":[94],"tracking,":[95],"which":[96],"leverages":[97],"region":[99],"proposal":[100,114],"network":[101],"novel":[104],"design.":[105],"Specifically,":[106],"our":[107,144],"method":[108,133,145],"can":[109],"jointly":[110],"exploit":[111],"discriminative":[112],"generation":[115],"structural":[117],"location":[123],"simple":[126],"feedforward":[127],"propagation.":[128],"We":[129],"evaluate":[130],"proposed":[132],"on":[134],"five":[135],"challenging":[136],"benchmarks,":[137],"extensive":[139],"experimental":[140],"results":[141],"demonstrate":[142],"that":[143],"performs":[146],"favorably":[147],"compared":[148],"with":[149,152],"state-of-the-art":[150],"respect":[153],"accuracy":[156],"speed.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
