{"id":"https://openalex.org/W2798075506","doi":"https://doi.org/10.1109/dicta.2017.8227487","title":"Robust Real-Time Visual Object Tracking via Multi-Scale Fully Convolutional Siamese Networks","display_name":"Robust Real-Time Visual Object Tracking via Multi-Scale Fully Convolutional Siamese Networks","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2798075506","doi":"https://doi.org/10.1109/dicta.2017.8227487","mag":"2798075506"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2017.8227487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2017.8227487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","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/A5101186603","display_name":"Longchao Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Longchao Yang","raw_affiliation_strings":["Xian Jiaotong University, Institute of Artificial Intelligence and Robotics, Xian, China"],"affiliations":[{"raw_affiliation_string":"Xian Jiaotong University, Institute of Artificial Intelligence and Robotics, Xian, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108651660","display_name":"Peilin Jiang","orcid":"https://orcid.org/0000-0003-0316-6631"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peilin Jiang","raw_affiliation_strings":["Xian Jiaotong University, Institute of Artificial Intelligence and Robotics, Xian, China"],"affiliations":[{"raw_affiliation_string":"Xian Jiaotong University, Institute of Artificial Intelligence and Robotics, Xian, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455958","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0003-3462-8472"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["Xian Jiaotong University, Institute of Artificial Intelligence and Robotics, Xian, China"],"affiliations":[{"raw_affiliation_string":"Xian Jiaotong University, Institute of Artificial Intelligence and Robotics, Xian, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101941896","display_name":"Xuan Wang","orcid":"https://orcid.org/0000-0003-1944-2346"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Wang","raw_affiliation_strings":["Xian Jiaotong University, Institute of Artificial Intelligence and Robotics, Xian, China"],"affiliations":[{"raw_affiliation_string":"Xian Jiaotong University, Institute of Artificial Intelligence and Robotics, Xian, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101186603"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.51593552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"25","issue":null,"first_page":"1","last_page":"7"},"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":0.9940000176429749,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7688742280006409},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7684899568557739},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7355837821960449},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.616706371307373},{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.59968501329422},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.5409354567527771},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5355242490768433},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5337938070297241},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.49796056747436523},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47490394115448},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4568212628364563},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4320107400417328}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7688742280006409},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7684899568557739},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7355837821960449},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.616706371307373},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.59968501329422},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.5409354567527771},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5355242490768433},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5337938070297241},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.49796056747436523},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47490394115448},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4568212628364563},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4320107400417328},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dicta.2017.8227487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2017.8227487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","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":44,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W809122546","https://openalex.org/W857627204","https://openalex.org/W1745334888","https://openalex.org/W1857884451","https://openalex.org/W1903029394","https://openalex.org/W1908905119","https://openalex.org/W1955514522","https://openalex.org/W1997121481","https://openalex.org/W2024029849","https://openalex.org/W2043767314","https://openalex.org/W2089961441","https://openalex.org/W2117539524","https://openalex.org/W2124211486","https://openalex.org/W2130026429","https://openalex.org/W2139047213","https://openalex.org/W2154889144","https://openalex.org/W2158592639","https://openalex.org/W2158917775","https://openalex.org/W2163605009","https://openalex.org/W2186330282","https://openalex.org/W2211629196","https://openalex.org/W2343187456","https://openalex.org/W2407521645","https://openalex.org/W2408241409","https://openalex.org/W2469582947","https://openalex.org/W2470394683","https://openalex.org/W2473868734","https://openalex.org/W2513005088","https://openalex.org/W2518013266","https://openalex.org/W2555182955","https://openalex.org/W2560023338","https://openalex.org/W2613718673","https://openalex.org/W2964111344","https://openalex.org/W2964253307","https://openalex.org/W6620707391","https://openalex.org/W6622964371","https://openalex.org/W6623530903","https://openalex.org/W6649598916","https://openalex.org/W6679027886","https://openalex.org/W6684191040","https://openalex.org/W6688149436","https://openalex.org/W6703518758","https://openalex.org/W6726293469"],"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/W3104472694","https://openalex.org/W2141888607","https://openalex.org/W72160640","https://openalex.org/W2753886513"],"abstract_inverted_index":{"Robust":[0],"visual":[1],"object":[2,117],"tracking":[3],"against":[4],"occlusions":[5,48],"and":[6,49,111,119],"deformations":[7,50],"is":[8,45,70],"still":[9],"very":[10],"challenging":[11],"task.":[12],"To":[13],"tackle":[14],"these":[15,85],"issues,":[16],"existing":[17],"Convolutional":[18,57],"Neural":[19],"Networks":[20],"(CNNs)":[21],"based":[22,51],"trackers":[23],"either":[24],"fail":[25],"to":[26,47,92],"handle":[27,113],"them":[28],"or":[29],"can":[30,112],"just":[31],"run":[32],"in":[33],"low":[34],"speed.":[35],"In":[36,62],"this":[37],"paper,":[38],"we":[39],"present":[40],"a":[41,53,99],"realtime":[42],"tracker":[43],"which":[44],"robust":[46],"on":[52,80,98],"Region-based,":[54],"Multi-Scale":[55],"Fully":[56],"Siamese":[58],"Network":[59],"(R-":[60],"MSFCN).":[61],"the":[63,66,74,96,114],"proposed":[64],"R-MSFCN,":[65],"information":[67],"of":[68,76,95,116],"regions":[69],"extracted":[71],"separately":[72],"by":[73],"proposition":[75],"position-sensitive":[77],"score":[78,86],"maps":[79,87],"multiple":[81],"convolutional":[82],"layers.":[83],"Combining":[84],"via":[88],"adaptive":[89],"weights":[90],"leads":[91],"accurate":[93],"location":[94],"target":[97],"new":[100],"frame.":[101],"The":[102],"experiments":[103],"illustrate":[104],"that":[105],"our":[106],"method":[107],"outperforms":[108],"state-of-the-art":[109],"approaches,":[110],"cases":[115],"deformation":[118],"occlusion":[120],"at":[121],"about":[122],"31":[123],"FPS.":[124]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
