{"id":"https://openalex.org/W4401416951","doi":"https://doi.org/10.1109/icra57147.2024.10611726","title":"Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models","display_name":"Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401416951","doi":"https://doi.org/10.1109/icra57147.2024.10611726"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10611726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5000324321","display_name":"Wen-Hsuan Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wen-Hsuan Chu","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019748928","display_name":"Adam W. Harley","orcid":"https://orcid.org/0000-0002-9851-4645"},"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":"Adam W. Harley","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040760890","display_name":"Pavel Tokmakov","orcid":"https://orcid.org/0000-0003-2043-6242"},"institutions":[{"id":"https://openalex.org/I4391768151","display_name":"Toyota Research Institute","ror":"https://ror.org/04fpkc108","country_code":null,"type":"facility","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4391768151"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Pavel Tokmakov","raw_affiliation_strings":["Toyota Research Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyota Research Institute","institution_ids":["https://openalex.org/I4391768151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045047925","display_name":"Achal Dave","orcid":"https://orcid.org/0000-0003-1948-5629"},"institutions":[{"id":"https://openalex.org/I4391768151","display_name":"Toyota Research Institute","ror":"https://ror.org/04fpkc108","country_code":null,"type":"facility","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4391768151"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Achal Dave","raw_affiliation_strings":["Toyota Research Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyota Research Institute","institution_ids":["https://openalex.org/I4391768151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065368881","display_name":"Leonidas Guibas","orcid":"https://orcid.org/0000-0002-8315-4886"},"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":"Leonidas Guibas","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008661738","display_name":"Katerina Fragkiadaki","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katerina Fragkiadaki","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4916","last_page":"4923"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10028","display_name":"Topic Modeling","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9976999759674072,"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":0.7141100168228149},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.6075654029846191},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.573554515838623},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5338367819786072},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5308676362037659},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.512299656867981},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34222882986068726}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7141100168228149},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6075654029846191},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.573554515838623},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5338367819786072},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5308676362037659},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.512299656867981},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34222882986068726},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10611726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1530781137","https://openalex.org/W1907877624","https://openalex.org/W1950703464","https://openalex.org/W2030346542","https://openalex.org/W2076756823","https://openalex.org/W2138302688","https://openalex.org/W2148958980","https://openalex.org/W2250539671","https://openalex.org/W2252355370","https://openalex.org/W2603203130","https://openalex.org/W2739491435","https://openalex.org/W2798569237","https://openalex.org/W2889986507","https://openalex.org/W2916743882","https://openalex.org/W2920942303","https://openalex.org/W2948672349","https://openalex.org/W2956985883","https://openalex.org/W2963227409","https://openalex.org/W2963936013","https://openalex.org/W2964347345","https://openalex.org/W2981393651","https://openalex.org/W2982723417","https://openalex.org/W2990205821","https://openalex.org/W2997998901","https://openalex.org/W3035672751","https://openalex.org/W3084173793","https://openalex.org/W3095753995","https://openalex.org/W3097885906","https://openalex.org/W3104218139","https://openalex.org/W3115390238","https://openalex.org/W3119686997","https://openalex.org/W3138516171","https://openalex.org/W3158120491","https://openalex.org/W3173859428","https://openalex.org/W3215023725","https://openalex.org/W4225544038","https://openalex.org/W4282919422","https://openalex.org/W4309864194","https://openalex.org/W4312396403","https://openalex.org/W4312424618","https://openalex.org/W4312509508","https://openalex.org/W4312547276","https://openalex.org/W4312567319","https://openalex.org/W4313007081","https://openalex.org/W4313026212","https://openalex.org/W4319300361","https://openalex.org/W4367000115","https://openalex.org/W4379474533","https://openalex.org/W4386065815","https://openalex.org/W4390874575","https://openalex.org/W4401416102","https://openalex.org/W4404612908","https://openalex.org/W6639102338","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6759534164","https://openalex.org/W6765565478","https://openalex.org/W6787985011","https://openalex.org/W6788023325","https://openalex.org/W6790019176","https://openalex.org/W6791353385","https://openalex.org/W6796524941","https://openalex.org/W6802517928","https://openalex.org/W6809716307","https://openalex.org/W6839745749","https://openalex.org/W6850787431","https://openalex.org/W6852276098","https://openalex.org/W6853702739"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W4298312966","https://openalex.org/W2158788032"],"abstract_inverted_index":{"Object":[0],"tracking":[1,33,259],"is":[2],"central":[3],"to":[4,12,153,182],"robot":[5],"perception":[6],"and":[7,50,53,90,101,117,140,147,173,235,253,260,279,285],"scene":[8],"understanding,":[9],"allowing":[10],"robots":[11],"parse":[13],"a":[14,28,97,109,156,277],"video":[15,77,111],"stream":[16],"in":[17,48,55,59,105,240,251],"terms":[18],"of":[19,34,128,169,190,199],"moving":[20],"objects":[21,52,212],"with":[22,121,131,164,178,291],"names.":[23],"Tracking-by-detection":[24],"has":[25],"long":[26],"been":[27],"dominant":[29],"paradigm":[30],"for":[31,75,136,256,267,282],"object":[32,36,104,116,145,192,258],"specific":[35],"categories":[37],"[1],":[38],"[2].":[39],"Recently,":[40],"large-scale":[41,70],"pre-trained":[42,71,134],"models":[43,74,135],"have":[44],"shown":[45],"promising":[46],"advances":[47],"detecting":[49],"segmenting":[51],"parts":[54],"2D":[56,106],"static":[57,72,137],"images":[58],"the":[60,64,126,161,165,170,179,184,188,196,200],"wild.":[61],"This":[62],"raises":[63],"question:":[65],"can":[66,236,274],"we":[67,82,142],"re-purpose":[68],"these":[69],"image":[73,138],"open-vocabulary":[76,85,144],"tracking?":[78],"In":[79,244],"this":[80],"paper,":[81],"combine":[83],"an":[84,175,191],"detector":[86],"[3],":[87],"segmenter":[88,177],"[4],":[89],"dense":[91],"optical":[92,207],"flow":[93,208],"estimator":[94],"[5],":[95],"into":[96],"model":[98,223,247],"that":[99,221,271],"tracks":[100,120,239],"segments":[102],"any":[103],"videos.":[107],"Given":[108],"monocular":[110],"input,":[112],"our":[113,222,246,272],"method":[114],"predicts":[115],"part":[118],"mask":[119],"associated":[122],"language":[123],"descriptions,":[124],"rebuilding":[125],"pipeline":[127],"Tractor":[129],"[6]":[130],"modern":[132],"large":[133],"detection":[139],"segmentation:":[141],"detect":[143],"instances":[146],"propagate":[148],"their":[149],"boxes":[150,163,202],"from":[151,289],"frame":[152,154],"using":[155,215],"flow-based":[157],"motion":[158],"model,":[159],"refine":[160],"propagated":[162,201],"box":[166,181],"regression":[167],"module":[168],"visual":[171],"detector,":[172],"prompt":[174],"open-world":[176,257],"refined":[180],"segment":[183],"objects.":[185,293],"We":[186,210,219,269],"decide":[187],"termination":[189],"track":[193],"based":[194],"on":[195,227],"objectness":[197],"score":[198],"as":[203,205,276],"well":[204],"forward-backward":[206],"consistency.":[209],"re-identify":[211],"across":[213],"occlusions":[214],"deep":[216],"feature":[217],"matching.":[218],"show":[220],"achieves":[224],"strong":[225],"performance":[226],"multiple":[228],"established":[229],"benchmarks":[230,255],"[7],":[231],"[8],":[232],"[9],":[233],"[10],":[234],"produce":[237],"reasonable":[238],"manipulation":[241],"data":[242],"[11].":[243],"particular,":[245],"outperforms":[248],"previous":[249],"state-of-the-art":[250],"UVO":[252],"BURST,":[254],"segmentation,":[261],"despite":[262],"never":[263],"being":[264],"explicitly":[265],"trained":[266],"tracking.":[268],"hope":[270],"approach":[273],"serve":[275],"simple":[278],"extensible":[280],"framework":[281],"future":[283],"research":[284],"enable":[286],"imitation":[287],"learning":[288],"videos":[290],"unconventional":[292]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
