{"id":"https://openalex.org/W2579024533","doi":"https://doi.org/10.1109/iccv.2017.41","title":"Tracking the Untrackable: Learning to Track Multiple Cues with Long-Term Dependencies","display_name":"Tracking the Untrackable: Learning to Track Multiple Cues with Long-Term Dependencies","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2579024533","doi":"https://doi.org/10.1109/iccv.2017.41","mag":"2579024533"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2017.41","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.41","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://infoscience.epfl.ch/handle/20.500.14299/139703","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102990724","display_name":"Amir Sadeghian","orcid":"https://orcid.org/0000-0001-9911-075X"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Amir Sadeghian","raw_affiliation_strings":["Stanford University"],"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068504559","display_name":"Alexandre Alahi","orcid":"https://orcid.org/0000-0002-5004-1498"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Alexandre Alahi","raw_affiliation_strings":["Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland"],"affiliations":[{"raw_affiliation_string":"Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042646536","display_name":"Silvio Savarese","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Silvio Savarese","raw_affiliation_strings":["Stanford University"],"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102990724"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":28.1184,"has_fulltext":false,"cited_by_count":576,"citation_normalized_percentile":{"value":0.99720037,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"300","last_page":"311"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T11963","display_name":"Impact of Light on Environment and Health","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9711999893188477,"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":0.8260036110877991},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8023719787597656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7193370461463928},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.625045657157898},{"id":"https://openalex.org/keywords/data-association","display_name":"Data association","score":0.5588960647583008},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5538378357887268},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4861711859703064},{"id":"https://openalex.org/keywords/sensory-cue","display_name":"Sensory cue","score":0.465654194355011},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4535925090312958},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4451528787612915},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.43112874031066895},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.41542795300483704},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40648597478866577},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.347958505153656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3325013220310211},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.31863319873809814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8260036110877991},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8023719787597656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7193370461463928},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.625045657157898},{"id":"https://openalex.org/C2983325608","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Data association","level":3,"score":0.5588960647583008},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5538378357887268},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4861711859703064},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.465654194355011},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4535925090312958},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4451528787612915},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.43112874031066895},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.41542795300483704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40648597478866577},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.347958505153656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3325013220310211},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.31863319873809814},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv.2017.41","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.41","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:infoscience.tind.io:230216","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/139703","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference proceedings"}],"best_oa_location":{"id":"pmh:oai:infoscience.tind.io:230216","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/139703","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference proceedings"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":114,"referenced_works":["https://openalex.org/W94861440","https://openalex.org/W181493107","https://openalex.org/W1482815597","https://openalex.org/W1499578337","https://openalex.org/W1528063097","https://openalex.org/W1531192956","https://openalex.org/W1536214225","https://openalex.org/W1571268436","https://openalex.org/W1590686026","https://openalex.org/W1677182931","https://openalex.org/W1857884451","https://openalex.org/W1905690492","https://openalex.org/W1928419358","https://openalex.org/W1949591461","https://openalex.org/W1972987664","https://openalex.org/W1982925187","https://openalex.org/W1989493360","https://openalex.org/W1991807052","https://openalex.org/W1999050017","https://openalex.org/W2000326692","https://openalex.org/W2020629258","https://openalex.org/W2022515186","https://openalex.org/W2023951840","https://openalex.org/W2035153336","https://openalex.org/W2044164936","https://openalex.org/W2055022211","https://openalex.org/W2056250745","https://openalex.org/W2056446365","https://openalex.org/W2065994824","https://openalex.org/W2068335629","https://openalex.org/W2070339405","https://openalex.org/W2082716591","https://openalex.org/W2083049794","https://openalex.org/W2098669323","https://openalex.org/W2101668106","https://openalex.org/W2109770203","https://openalex.org/W2111644456","https://openalex.org/W2115739848","https://openalex.org/W2121091546","https://openalex.org/W2121193292","https://openalex.org/W2122469558","https://openalex.org/W2123534796","https://openalex.org/W2137788460","https://openalex.org/W2140137670","https://openalex.org/W2141461755","https://openalex.org/W2146183743","https://openalex.org/W2147953023","https://openalex.org/W2150298366","https://openalex.org/W2159998603","https://openalex.org/W2160372277","https://openalex.org/W2166563909","https://openalex.org/W2167052694","https://openalex.org/W2169282617","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2205690070","https://openalex.org/W2217690257","https://openalex.org/W2220271458","https://openalex.org/W2225887246","https://openalex.org/W2237765446","https://openalex.org/W2252862078","https://openalex.org/W2260975248","https://openalex.org/W2291627510","https://openalex.org/W2300840837","https://openalex.org/W2398802088","https://openalex.org/W2402606673","https://openalex.org/W2413071142","https://openalex.org/W2424778531","https://openalex.org/W2471048925","https://openalex.org/W2474013209","https://openalex.org/W2477869242","https://openalex.org/W2491664569","https://openalex.org/W2494577018","https://openalex.org/W2508815980","https://openalex.org/W2510977782","https://openalex.org/W2511791013","https://openalex.org/W2512465678","https://openalex.org/W2517710169","https://openalex.org/W2519586580","https://openalex.org/W2520234541","https://openalex.org/W2532363096","https://openalex.org/W2532516272","https://openalex.org/W2534527426","https://openalex.org/W2543696449","https://openalex.org/W2547098537","https://openalex.org/W2548601959","https://openalex.org/W2555375762","https://openalex.org/W2949968531","https://openalex.org/W2963165299","https://openalex.org/W2964015640","https://openalex.org/W2964253307","https://openalex.org/W4295331127","https://openalex.org/W6607209805","https://openalex.org/W6628681060","https://openalex.org/W6632098450","https://openalex.org/W6634116786","https://openalex.org/W6639772948","https://openalex.org/W6650413978","https://openalex.org/W6667782953","https://openalex.org/W6676780830","https://openalex.org/W6678298392","https://openalex.org/W6680598823","https://openalex.org/W6683692917","https://openalex.org/W6692671535","https://openalex.org/W6703518758","https://openalex.org/W6712210154","https://openalex.org/W6712737577","https://openalex.org/W6715434296","https://openalex.org/W6722869231","https://openalex.org/W6725245947","https://openalex.org/W6725558437","https://openalex.org/W6725898459","https://openalex.org/W6726469348","https://openalex.org/W6729143321"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W3017902212","https://openalex.org/W2964335273","https://openalex.org/W3014558862","https://openalex.org/W2265978784"],"abstract_inverted_index":{"The":[0],"majority":[1],"of":[2,19,44,71,104],"existing":[3],"solutions":[4],"to":[5,48,89],"the":[6,102,130],"Multi-Target":[7],"Tracking":[8],"(MTT)":[9],"problem":[10],"do":[11],"not":[12],"combine":[13],"cues":[14,81],"over":[15,82],"a":[16,22,69,83],"long":[17],"period":[18],"time":[20],"in":[21],"coherent":[23],"fashion.":[24],"In":[25],"this":[26,65],"paper,":[27],"we":[28,67],"present":[29,68],"an":[30],"online":[31],"method":[32,87,120],"that":[33,76],"encodes":[34],"long-term":[35],"temporal":[36,84],"dependencies":[37],"across":[38],"multiple":[39,80,110,125],"cues.":[40],"One":[41],"key":[42],"challenge":[43],"tracking":[45,109],"methods":[46],"is":[47],"accurately":[49],"track":[50],"occluded":[51,98],"targets":[52,111],"or":[53],"those":[54],"which":[55],"share":[56],"similar":[57],"appearance":[58],"properties":[59],"with":[60],"surrounding":[61],"objects.":[62],"To":[63],"address":[64],"challenge,":[66],"structure":[70],"Recurrent":[72],"Neural":[73],"Networks":[74],"(RNN)":[75],"jointly":[77],"reasons":[78],"on":[79,124],"window.":[85],"Our":[86,119],"allows":[88],"correct":[90],"data":[91],"association":[92],"errors":[93],"and":[94,116],"recover":[95],"observations":[96],"from":[97],"states.":[99],"We":[100],"demonstrate":[101],"robustness":[103],"our":[105],"data-driven":[106],"approach":[107],"by":[108],"using":[112],"their":[113],"appearance,":[114],"motion,":[115],"even":[117],"interactions.":[118],"outperforms":[121],"previous":[122],"works":[123],"publicly":[126],"available":[127],"datasets":[128],"including":[129],"challenging":[131],"MOT":[132],"benchmark.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":48},{"year":2022,"cited_by_count":74},{"year":2021,"cited_by_count":107},{"year":2020,"cited_by_count":127},{"year":2019,"cited_by_count":101},{"year":2018,"cited_by_count":64},{"year":2017,"cited_by_count":12}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}