{"id":"https://openalex.org/W4285102230","doi":"https://doi.org/10.1109/icra46639.2022.9812327","title":"SiamX: An Efficient Long-term Tracker Using Cross-level Feature Correlation and Adaptive Tracking Scheme","display_name":"SiamX: An Efficient Long-term Tracker Using Cross-level Feature Correlation and Adaptive Tracking Scheme","publication_year":2022,"publication_date":"2022-05-23","ids":{"openalex":"https://openalex.org/W4285102230","doi":"https://doi.org/10.1109/icra46639.2022.9812327"},"language":"en","primary_location":{"id":"doi:10.1109/icra46639.2022.9812327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9812327","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Robotics and Automation (ICRA)","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/A5035324795","display_name":"Huajian Huang","orcid":"https://orcid.org/0000-0002-0963-1146"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Huajian Huang","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Department of Computer Science and Engineering","Department of Computer Science and Engineering, The Hong Kong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Department of Computer Science and Engineering","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, The Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027689970","display_name":"Sai-Kit Yeung","orcid":"https://orcid.org/0000-0001-7974-0607"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sai-Kit Yeung","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Department of Computer Science and Engineering","Department of Computer Science and Engineering, The Hong Kong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Department of Computer Science and Engineering","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, The Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035324795"],"corresponding_institution_ids":["https://openalex.org/I200769079"],"apc_list":null,"apc_paid":null,"fwci":0.1791,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49194636,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1237","last_page":"1243"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9891999959945679,"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":0.9799000024795532,"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/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.830170750617981},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7378637790679932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7333733439445496},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.7199671268463135},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6524330377578735},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5998660922050476},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5351458787918091},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.5345050096511841},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5037638545036316},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.48051154613494873},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.47726958990097046},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4629361033439636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41269704699516296},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.339143306016922},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1304926872253418}],"concepts":[{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.830170750617981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7378637790679932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7333733439445496},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.7199671268463135},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6524330377578735},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5998660922050476},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5351458787918091},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.5345050096511841},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5037638545036316},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.48051154613494873},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.47726958990097046},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4629361033439636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41269704699516296},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.339143306016922},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1304926872253418},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra46639.2022.9812327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9812327","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-119301","is_oa":false,"landing_page_url":"http://www.scopus.com/record/display.url?eid=2-s2.0-85136328851&origin=inward","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4884566779","display_name":null,"funder_award_id":"R9429","funder_id":"https://openalex.org/F4320323537","funder_display_name":"Hong Kong University of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320323537","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1857884451","https://openalex.org/W1861492603","https://openalex.org/W2117539524","https://openalex.org/W2126302311","https://openalex.org/W2132083787","https://openalex.org/W2194775991","https://openalex.org/W2214352687","https://openalex.org/W2408241409","https://openalex.org/W2470394683","https://openalex.org/W2504335775","https://openalex.org/W2565639579","https://openalex.org/W2794744029","https://openalex.org/W2799058067","https://openalex.org/W2886910176","https://openalex.org/W2891033863","https://openalex.org/W2898200825","https://openalex.org/W2937749627","https://openalex.org/W2962824803","https://openalex.org/W2963074722","https://openalex.org/W2963534981","https://openalex.org/W2963840672","https://openalex.org/W2964253307","https://openalex.org/W2966759264","https://openalex.org/W2982770724","https://openalex.org/W2990187711","https://openalex.org/W2998027361","https://openalex.org/W3001584168","https://openalex.org/W3034440418","https://openalex.org/W3035211844","https://openalex.org/W3035453691","https://openalex.org/W3035571898","https://openalex.org/W3108235634","https://openalex.org/W3108519869","https://openalex.org/W3131625634","https://openalex.org/W6639102338","https://openalex.org/W6678515836","https://openalex.org/W6688356126","https://openalex.org/W6696085341","https://openalex.org/W6755863804","https://openalex.org/W6776119668","https://openalex.org/W6780018109"],"related_works":["https://openalex.org/W4312791623","https://openalex.org/W2385949326","https://openalex.org/W2534746541","https://openalex.org/W2789220062","https://openalex.org/W2422898642","https://openalex.org/W4307010368","https://openalex.org/W2820058250","https://openalex.org/W4286251267","https://openalex.org/W2396101943","https://openalex.org/W3126660769"],"abstract_inverted_index":{"Siamese":[0,96],"network":[1],"based":[2],"trackers":[3],"have":[4],"achieved":[5],"significant":[6],"progress":[7],"in":[8,61],"visual":[9],"object":[10],"tracking.":[11],"For":[12],"the":[13,38,78,103,139],"sake":[14],"of":[15,53,63,70],"speed,":[16],"they":[17,41],"mainly":[18],"rely":[19],"on":[20,125],"offline":[21],"training":[22],"to":[23,46,90,98,114,142],"learn":[24,99],"a":[25,30,34,43,85],"mono-level":[26],"feature":[27],"correlation":[28],"between":[29,102],"target":[31,48,54,75,104,121],"template":[32,105],"and":[33,77,106,109,118,132,145,147],"search":[35,107],"region.":[36],"During":[37],"tracking":[39,87,116],"period,":[40],"use":[42],"fixed":[44],"strategy":[45],"infer":[47],"positions":[49],"over":[50],"sequences":[51],"regardless":[52],"states.":[55],"However,":[56],"such":[57],"approaches":[58],"are":[59],"vulnerable":[60],"case":[62],"long-term":[64],"challenges":[65],"e.g.":[66],"large":[67],"variance,":[68],"presence":[69],"distractors,":[71],"fast":[72,120],"motion,":[73],"or":[74],"disappearing":[76],"like.":[79],"In":[80],"this":[81],"paper,":[82],"we":[83],"propose":[84],"new":[86],"framework,":[88],"referred":[89],"as":[91],"SiamX,":[92],"by":[93],"exploiting":[94],"cross-level":[95],"features":[97],"robust":[100],"correlations":[101],"regions,":[108],"also":[110],"adaptive":[111],"inference":[112],"strategies":[113],"prevent":[115],"loss":[117],"realize":[119],"re-localization.":[122],"Extensive":[123],"experiments":[124],"four":[126],"benchmarks":[127],"including":[128],"VOT-2019,":[129],"LaSOT,":[130],"GOT-10k,":[131],"TrackingNet":[133],"show":[134],"our":[135],"method":[136],"significantly":[137],"enhances":[138],"tracker's":[140],"ability":[141],"resist":[143],"variance":[144],"interference,":[146],"achieve":[148],"state-of-the-art":[149],"results":[150],"at":[151],"around":[152],"50":[153],"FPS.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}