{"id":"https://openalex.org/W4385575022","doi":"https://doi.org/10.1109/tpami.2023.3301975","title":"QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking","display_name":"QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385575022","doi":"https://doi.org/10.1109/tpami.2023.3301975","pmid":"https://pubmed.ncbi.nlm.nih.gov/37540611"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3301975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3301975","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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/A5084005703","display_name":"Tobias Fischer","orcid":"https://orcid.org/0000-0001-8227-001X"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Tobias Fischer","raw_affiliation_strings":["Department of Information Technology and Electrical Engineering, ETH Zurich, Z&#x00FC;rich, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-8227-001X","affiliations":[{"raw_affiliation_string":"Department of Information Technology and Electrical Engineering, ETH Zurich, Z&#x00FC;rich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079218468","display_name":"T. Huang","orcid":"https://orcid.org/0000-0002-6390-7262"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Thomas E. Huang","raw_affiliation_strings":["Department of Information Technology and Electrical Engineering, ETH Zurich, Z&#x00FC;rich, Switzerland"],"raw_orcid":"https://orcid.org/0000-0002-6390-7262","affiliations":[{"raw_affiliation_string":"Department of Information Technology and Electrical Engineering, ETH Zurich, Z&#x00FC;rich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020672335","display_name":"Jiangmiao Pang","orcid":"https://orcid.org/0000-0002-6711-9319"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangmiao Pang","raw_affiliation_strings":["Shanghai AI Laboratory, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6711-9319","affiliations":[{"raw_affiliation_string":"Shanghai AI Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003617960","display_name":"Linlu Qiu","orcid":"https://orcid.org/0000-0002-1696-5419"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Linlu Qiu","raw_affiliation_strings":["Department of EECS, Massachusetts Institute of Technology, Cambridge, MA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1696-5419","affiliations":[{"raw_affiliation_string":"Department of EECS, Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101730466","display_name":"Haofeng Chen","orcid":"https://orcid.org/0000-0002-6036-5744"},"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":"Haofeng Chen","raw_affiliation_strings":["Computer Science Department, Stanford University, Stanford, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-6036-5744","affiliations":[{"raw_affiliation_string":"Computer Science Department, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029105520","display_name":"Trevor Darrell","orcid":"https://orcid.org/0000-0001-5453-8533"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trevor Darrell","raw_affiliation_strings":["Department of EECS, UC Berkeley, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-5453-8533","affiliations":[{"raw_affiliation_string":"Department of EECS, UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067487326","display_name":"Fisher Yu","orcid":"https://orcid.org/0000-0001-8829-7344"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Fisher Yu","raw_affiliation_strings":["Department of Information Technology and Electrical Engineering, ETH Zurich, Z&#x00FC;rich, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-8829-7344","affiliations":[{"raw_affiliation_string":"Department of Information Technology and Electrical Engineering, ETH Zurich, Z&#x00FC;rich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5084005703"],"corresponding_institution_ids":["https://openalex.org/I35440088"],"apc_list":null,"apc_paid":null,"fwci":13.8078,"has_fulltext":false,"cited_by_count":122,"citation_normalized_percentile":{"value":0.99319701,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"45","issue":"12","first_page":"15380","last_page":"15393"},"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/T11448","display_name":"Face recognition and analysis","score":0.9904000163078308,"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/T11812","display_name":"Nasal Surgery and Airway Studies","score":0.9412999749183655,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.788953423500061},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.703254222869873},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.6650683879852295},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6605045795440674},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5743998885154724},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.539081335067749},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5314604043960571},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.49686339497566223},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4621812105178833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4565353989601135},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4520811438560486},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4500308036804199},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4266952872276306},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4236741065979004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.394593209028244},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17343184351921082},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13683855533599854}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.788953423500061},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.703254222869873},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.6650683879852295},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6605045795440674},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5743998885154724},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.539081335067749},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5314604043960571},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.49686339497566223},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4621812105178833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4565353989601135},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4520811438560486},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4500308036804199},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4266952872276306},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4236741065979004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.394593209028244},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17343184351921082},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13683855533599854},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3301975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3301975","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37540611","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37540611","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":119,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1531192956","https://openalex.org/W1590686026","https://openalex.org/W1966408213","https://openalex.org/W2035153336","https://openalex.org/W2083049794","https://openalex.org/W2111644456","https://openalex.org/W2124781496","https://openalex.org/W2138621090","https://openalex.org/W2150095155","https://openalex.org/W2150298366","https://openalex.org/W2174962631","https://openalex.org/W2194775991","https://openalex.org/W2237765446","https://openalex.org/W2252355370","https://openalex.org/W2291627510","https://openalex.org/W2470394683","https://openalex.org/W2511791013","https://openalex.org/W2534578893","https://openalex.org/W2555897561","https://openalex.org/W2565639579","https://openalex.org/W2579024533","https://openalex.org/W2594507094","https://openalex.org/W2598634450","https://openalex.org/W2601564443","https://openalex.org/W2603203130","https://openalex.org/W2739013603","https://openalex.org/W2749203358","https://openalex.org/W2765407302","https://openalex.org/W2766984662","https://openalex.org/W2798542761","https://openalex.org/W2798991696","https://openalex.org/W2895071559","https://openalex.org/W2920942303","https://openalex.org/W2944828972","https://openalex.org/W2948012107","https://openalex.org/W2948672349","https://openalex.org/W2962721361","https://openalex.org/W2962855257","https://openalex.org/W2963063317","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2963402313","https://openalex.org/W2964015640","https://openalex.org/W2964253307","https://openalex.org/W2964333437","https://openalex.org/W2977487707","https://openalex.org/W2981393651","https://openalex.org/W2982723417","https://openalex.org/W3005680577","https://openalex.org/W3012922853","https://openalex.org/W3034303554","https://openalex.org/W3035172746","https://openalex.org/W3035323039","https://openalex.org/W3035410385","https://openalex.org/W3035524453","https://openalex.org/W3035564946","https://openalex.org/W3042011474","https://openalex.org/W3086436251","https://openalex.org/W3095753995","https://openalex.org/W3095862565","https://openalex.org/W3096068180","https://openalex.org/W3097885906","https://openalex.org/W3100953775","https://openalex.org/W3104218139","https://openalex.org/W3104778224","https://openalex.org/W3106763294","https://openalex.org/W3108655343","https://openalex.org/W3109372619","https://openalex.org/W3113093028","https://openalex.org/W3115390238","https://openalex.org/W3119686997","https://openalex.org/W3121162167","https://openalex.org/W3136115421","https://openalex.org/W3165926952","https://openalex.org/W3167949052","https://openalex.org/W3173446152","https://openalex.org/W3184439416","https://openalex.org/W3190647944","https://openalex.org/W4213179364","https://openalex.org/W4250482878","https://openalex.org/W4286904999","https://openalex.org/W4297808394","https://openalex.org/W4310746146","https://openalex.org/W4312473433","https://openalex.org/W4312509508","https://openalex.org/W4312689495","https://openalex.org/W4313072323","https://openalex.org/W4319299988","https://openalex.org/W4319866011","https://openalex.org/W4386076204","https://openalex.org/W4386076331","https://openalex.org/W6620707391","https://openalex.org/W6659566489","https://openalex.org/W6696672603","https://openalex.org/W6730323794","https://openalex.org/W6735531217","https://openalex.org/W6745136726","https://openalex.org/W6750697433","https://openalex.org/W6760424586","https://openalex.org/W6763416564","https://openalex.org/W6763442200","https://openalex.org/W6768435530","https://openalex.org/W6774314701","https://openalex.org/W6775253321","https://openalex.org/W6787985011","https://openalex.org/W6788023325","https://openalex.org/W6788734293","https://openalex.org/W6795368335","https://openalex.org/W6797162190","https://openalex.org/W6798838024","https://openalex.org/W6799693209","https://openalex.org/W6802459829","https://openalex.org/W6804053623","https://openalex.org/W6809649412","https://openalex.org/W6810701631","https://openalex.org/W6810827814","https://openalex.org/W6844194202","https://openalex.org/W6847073259"],"related_works":["https://openalex.org/W2109424811","https://openalex.org/W4246757943","https://openalex.org/W2375480909","https://openalex.org/W2353314428","https://openalex.org/W2381195555","https://openalex.org/W2012019886","https://openalex.org/W2155354516","https://openalex.org/W2965594636","https://openalex.org/W4387185219","https://openalex.org/W2912550626"],"abstract_inverted_index":{"Similarity":[0,44],"learning":[1,65,112],"has":[2],"been":[3],"recognized":[4],"as":[5,24],"a":[6,54,94,131,148,174],"crucial":[7],"step":[8],"for":[9,58,102],"object":[10,15,51,69,103],"tracking.":[11],"However,":[12],"existing":[13,68],"multiple":[14,67],"tracking":[16,133,141,167],"methods":[17,168],"only":[18],"use":[19],"sparse":[20],"ground":[21],"truth":[22],"matching":[23],"the":[25,30,33,88,163,178,189],"training":[26,136],"objective,":[27],"while":[28,183],"ignoring":[29],"majority":[31],"of":[32,50,56,151,165],"informative":[34],"regions":[35,52],"in":[36],"images.":[37],"In":[38,105],"this":[39,63],"paper,":[40],"we":[41,107],"present":[42],"Quasi-Dense":[43,73],"Learning,":[45],"which":[46,76],"densely":[47],"samples":[48],"hundreds":[49],"on":[53,137,147,169,177],"pair":[55],"images":[57],"contrastive":[59],"learning.":[60],"We":[61,85,143,155],"combine":[62],"similarity":[64,111,125],"with":[66],"detectors":[70],"to":[71,117,188],"build":[72],"Tracking":[74],"(QDTrack),":[75],"does":[77],"not":[78,115],"require":[79],"displacement":[80],"regression":[81],"or":[82,139],"motion":[83],"priors.":[84],"find":[86,156],"that":[87,109],"resulting":[89],"distinctive":[90],"feature":[91],"space":[92],"admits":[93],"simple":[95],"nearest":[96],"neighbor":[97],"search":[98],"at":[99],"inference":[100],"time":[101],"association.":[104],"addition,":[106],"show":[108],"our":[110],"scheme":[113],"is":[114],"limited":[116],"video":[118],"data,":[119],"but":[120],"can":[121],"learn":[122],"effective":[123],"instance":[124],"even":[126],"from":[127],"static":[128],"input,":[129],"enabling":[130],"competitive":[132],"performance":[134,164],"without":[135],"videos":[138],"using":[140],"supervision.":[142],"conduct":[144],"extensive":[145],"experiments":[146],"wide":[149],"variety":[150],"popular":[152],"MOT":[153,181],"benchmarks.":[154],"that,":[157],"despite":[158],"its":[159],"simplicity,":[160],"QDTrack":[161],"rivals":[162],"state-of-the-art":[166,176],"all":[170],"benchmarks":[171],"and":[172],"sets":[173],"new":[175],"large-scale":[179],"BDD100K":[180],"benchmark,":[182],"introducing":[184],"negligible":[185],"computational":[186],"overhead":[187],"detector.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":16},{"year":2025,"cited_by_count":60},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":8}],"updated_date":"2026-05-31T08:46:17.908082","created_date":"2025-10-10T00:00:00"}
