{"id":"https://openalex.org/W3036133893","doi":"https://doi.org/10.1109/cvprw50498.2020.00525","title":"LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking","display_name":"LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3036133893","doi":"https://doi.org/10.1109/cvprw50498.2020.00525","mag":"3036133893"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw50498.2020.00525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw50498.2020.00525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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/A5082349270","display_name":"Guanghan Ning","orcid":"https://orcid.org/0000-0002-4356-7862"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Guanghan Ning","raw_affiliation_strings":["JD Finance America Corporation"],"affiliations":[{"raw_affiliation_string":"JD Finance America Corporation","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062247330","display_name":"Jian Pei","orcid":"https://orcid.org/0000-0002-2200-8711"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jian Pei","raw_affiliation_strings":["Simon Fraser University"],"affiliations":[{"raw_affiliation_string":"Simon Fraser University","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060016795","display_name":"Heng Huang","orcid":"https://orcid.org/0000-0002-3483-8333"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heng Huang","raw_affiliation_strings":["JD Finance America Corporation"],"affiliations":[{"raw_affiliation_string":"JD Finance America Corporation","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5082349270"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.8389,"has_fulltext":false,"cited_by_count":95,"citation_normalized_percentile":{"value":0.9770283,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4456","last_page":"4465"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","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/T10812","display_name":"Human Pose and Action Recognition","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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962999820709229,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.811797022819519},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7273555397987366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6670832633972168},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5980607271194458},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.558621883392334},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5263009071350098},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.4588925838470459},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44046714901924133},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.43884554505348206},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.43603354692459106},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.429876446723938},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.41985422372817993},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.41365110874176025},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.32964223623275757},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16906878352165222},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.091045081615448},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08903560042381287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.811797022819519},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7273555397987366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6670832633972168},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5980607271194458},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.558621883392334},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5263009071350098},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.4588925838470459},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44046714901924133},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.43884554505348206},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.43603354692459106},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.429876446723938},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.41985422372817993},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.41365110874176025},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.32964223623275757},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16906878352165222},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.091045081615448},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08903560042381287},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvprw50498.2020.00525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw50498.2020.00525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W2080873731","https://openalex.org/W2124781496","https://openalex.org/W2135533529","https://openalex.org/W2194775991","https://openalex.org/W2307770531","https://openalex.org/W2554082199","https://openalex.org/W2559085405","https://openalex.org/W2559320744","https://openalex.org/W2565639579","https://openalex.org/W2578797046","https://openalex.org/W2601564443","https://openalex.org/W2620105270","https://openalex.org/W2742737904","https://openalex.org/W2769833683","https://openalex.org/W2788996589","https://openalex.org/W2798721181","https://openalex.org/W2886335102","https://openalex.org/W2895150009","https://openalex.org/W2916798096","https://openalex.org/W2950800384","https://openalex.org/W2952819818","https://openalex.org/W2959975024","https://openalex.org/W2962954622","https://openalex.org/W2963076818","https://openalex.org/W2963150697","https://openalex.org/W2963197583","https://openalex.org/W2963402313","https://openalex.org/W2963708869","https://openalex.org/W2963781481","https://openalex.org/W2963927307","https://openalex.org/W2964070329","https://openalex.org/W2964084369","https://openalex.org/W2964185410","https://openalex.org/W2964221239","https://openalex.org/W2964304707","https://openalex.org/W2965326519","https://openalex.org/W4289047567","https://openalex.org/W4295295532","https://openalex.org/W6692078629","https://openalex.org/W6697925102","https://openalex.org/W6714138976","https://openalex.org/W6730410022","https://openalex.org/W6738297968","https://openalex.org/W6748349140","https://openalex.org/W6748370023","https://openalex.org/W6750247337","https://openalex.org/W6750378959","https://openalex.org/W6750584947","https://openalex.org/W6753494528","https://openalex.org/W6755436981","https://openalex.org/W6757733370"],"related_works":["https://openalex.org/W2371352078","https://openalex.org/W2953461625","https://openalex.org/W2077383796","https://openalex.org/W2080136900","https://openalex.org/W2372768926","https://openalex.org/W2999799752","https://openalex.org/W2054458431","https://openalex.org/W3013576436","https://openalex.org/W2115167491","https://openalex.org/W2799161558"],"abstract_inverted_index":{"In":[0,128],"this":[1],"paper,":[2],"we":[3,112,134],"propose":[4,113],"a":[5,70,78,114,125,136],"simple":[6],"yet":[7],"effective":[8],"framework,":[9],"named":[10],"LightTrack,":[11],"for":[12,53,120,142],"online":[13,52,72,94,190],"human":[14,21,121,140,149,165],"pose":[15,23,31,81,122,150,176],"tracking.":[16],"Existing":[17],"methods":[18,191,199],"usually":[19],"perform":[20],"detection,":[22],"estimation":[24],"and":[25,50,62,97,152,178,192,206],"tracking":[26,32,105],"in":[27],"sequential":[28],"stages,":[29],"where":[30],"is":[33,44,153,157,170,193],"regarded":[34],"as":[35,69,124],"an":[36],"offline":[37,85,197],"bipartite":[38],"matching":[39,123,180],"problem.":[40],"Our":[41],"proposed":[42,168],"framework":[43,89,169],"designed":[45],"to":[46,130,159,173],"be":[47],"generic,":[48],"efficient":[49],"truly":[51],"top-down":[54],"approaches.":[55],"For":[56],"efficiency,":[57],"Single-Person":[58],"Pose":[59],"Tracking":[60,65,109],"(SPT)":[61],"Visual":[63],"Object":[64,108],"(VOT)":[66],"are":[67,208],"incorporated":[68],"unified":[71],"functioning":[73],"entity,":[74],"easily":[75],"implemented":[76],"by":[77],"replaceable":[79],"single-person":[80],"estimator.":[82],"To":[83],"mitigate":[84],"optimization":[86],"costs,":[87],"the":[88],"also":[90],"unifies":[91],"SPT":[92],"with":[93,106,196],"identity":[95],"association":[96],"sheds":[98],"first":[99],"light":[100],"upon":[101],"bridging":[102],"multiperson":[103],"keypoint":[104],"Multi-Target":[107],"(MOT).":[110],"Specifically,":[111],"Siamese":[115],"Graph":[116],"Convolution":[117],"Network":[118],"(SGCN)":[119],"Re-ID":[126,132],"module.":[127],"contrary":[129],"other":[131,175,189],"modules,":[133],"use":[135],"graphical":[137],"representation":[138,146],"of":[139],"joints":[141],"matching.":[143],"The":[144,167],"skeleton-based":[145],"effectively":[147],"captures":[148],"similarity":[151],"computationally":[154],"inexpensive.":[155],"It":[156],"robust":[158],"sudden":[160],"camera":[161],"shifts":[162],"that":[163,185],"introduce":[164],"drifting.":[166],"general":[171],"enough":[172],"fit":[174],"estimators":[177],"candidate":[179],"mechanisms.":[181],"Extensive":[182],"experiments":[183],"show":[184],"our":[186],"method":[187],"outperforms":[188],"very":[194],"competitive":[195],"state-of-the-art":[198],"while":[200],"maintaining":[201],"higher":[202],"frame":[203],"rates.":[204],"Code":[205],"models":[207],"publicly":[209],"available":[210],"at":[211],"https://github.com/Guanghan/lighttrack.":[212]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":19}],"updated_date":"2026-01-29T23:13:10.619473","created_date":"2025-10-10T00:00:00"}
