{"id":"https://openalex.org/W3149485574","doi":"https://doi.org/10.1109/lra.2021.3068925","title":"PTP: Parallelized Tracking and Prediction With Graph Neural Networks and Diversity Sampling","display_name":"PTP: Parallelized Tracking and Prediction With Graph Neural Networks and Diversity Sampling","publication_year":2021,"publication_date":"2021-03-26","ids":{"openalex":"https://openalex.org/W3149485574","doi":"https://doi.org/10.1109/lra.2021.3068925","mag":"3149485574"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2021.3068925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3068925","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Robotics and Automation Letters","raw_type":"journal-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/A5090287059","display_name":"Xinshuo Weng","orcid":"https://orcid.org/0000-0002-7894-4381"},"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":"Xinshuo Weng","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081199756","display_name":"Ye Yuan","orcid":"https://orcid.org/0000-0001-5316-6002"},"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":"Ye Yuan","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037322163","display_name":"Kris Kitani","orcid":"https://orcid.org/0000-0002-9389-4060"},"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":"Kris Kitani","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":5.2424,"has_fulltext":false,"cited_by_count":74,"citation_normalized_percentile":{"value":0.96901756,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"6","issue":"3","first_page":"4640","last_page":"4647"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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":0.9994999766349792,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9979000091552734,"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":0.7686977386474609},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6653302907943726},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6386072635650635},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6247097253799438},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.585406482219696},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5588038563728333},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5306645035743713},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5238873362541199},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4679861068725586},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44019076228141785},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4300099015235901},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42348572611808777},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34536033868789673},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3424907922744751},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.18973800539970398},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.13007158041000366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7686977386474609},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6653302907943726},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6386072635650635},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6247097253799438},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.585406482219696},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5588038563728333},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5306645035743713},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5238873362541199},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4679861068725586},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44019076228141785},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4300099015235901},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42348572611808777},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34536033868789673},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3424907922744751},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.18973800539970398},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.13007158041000366},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2021.3068925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3068925","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308258","display_name":"Qualcomm","ror":"https://ror.org/002zrf773"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":97,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1846689784","https://openalex.org/W1913984289","https://openalex.org/W2092720120","https://openalex.org/W2115857089","https://openalex.org/W2150066425","https://openalex.org/W2222512263","https://openalex.org/W2291627510","https://openalex.org/W2424778531","https://openalex.org/W2519586580","https://openalex.org/W2560609797","https://openalex.org/W2606884824","https://openalex.org/W2607296803","https://openalex.org/W2739748921","https://openalex.org/W2772328249","https://openalex.org/W2798930779","https://openalex.org/W2806331055","https://openalex.org/W2811025443","https://openalex.org/W2894978157","https://openalex.org/W2898900571","https://openalex.org/W2902159581","https://openalex.org/W2903782687","https://openalex.org/W2905385096","https://openalex.org/W2910135751","https://openalex.org/W2911273949","https://openalex.org/W2940457086","https://openalex.org/W2948246283","https://openalex.org/W2949708697","https://openalex.org/W2949767467","https://openalex.org/W2950304053","https://openalex.org/W2954137266","https://openalex.org/W2962101532","https://openalex.org/W2962810718","https://openalex.org/W2962879692","https://openalex.org/W2962945412","https://openalex.org/W2963001155","https://openalex.org/W2963319519","https://openalex.org/W2963746531","https://openalex.org/W2963865839","https://openalex.org/W2963906196","https://openalex.org/W2964000524","https://openalex.org/W2965376383","https://openalex.org/W2968008415","https://openalex.org/W2969987486","https://openalex.org/W2970219816","https://openalex.org/W2971306974","https://openalex.org/W2971510799","https://openalex.org/W2972321983","https://openalex.org/W2982745079","https://openalex.org/W2983227562","https://openalex.org/W2985871763","https://openalex.org/W2989738721","https://openalex.org/W2989851631","https://openalex.org/W2991583626","https://openalex.org/W2994612440","https://openalex.org/W3009150298","https://openalex.org/W3022478135","https://openalex.org/W3034739212","https://openalex.org/W3034782805","https://openalex.org/W3035574168","https://openalex.org/W3037376004","https://openalex.org/W3103014337","https://openalex.org/W3104641012","https://openalex.org/W3108262631","https://openalex.org/W3114753236","https://openalex.org/W3132607695","https://openalex.org/W3207452968","https://openalex.org/W4287373991","https://openalex.org/W4288287716","https://openalex.org/W4295521014","https://openalex.org/W4301504317","https://openalex.org/W6639086153","https://openalex.org/W6639898247","https://openalex.org/W6677302653","https://openalex.org/W6696672603","https://openalex.org/W6720019270","https://openalex.org/W6726469348","https://openalex.org/W6733322467","https://openalex.org/W6735913928","https://openalex.org/W6740017579","https://openalex.org/W6741832134","https://openalex.org/W6745535286","https://openalex.org/W6751936687","https://openalex.org/W6754877132","https://openalex.org/W6755864109","https://openalex.org/W6756925679","https://openalex.org/W6758151150","https://openalex.org/W6762473954","https://openalex.org/W6763675009","https://openalex.org/W6765361892","https://openalex.org/W6766065261","https://openalex.org/W6767379092","https://openalex.org/W6767688279","https://openalex.org/W6774842091","https://openalex.org/W6779950659","https://openalex.org/W6781269497","https://openalex.org/W6802697897"],"related_works":["https://openalex.org/W4396941953","https://openalex.org/W2093104230","https://openalex.org/W2987280934","https://openalex.org/W4390874210","https://openalex.org/W4384918963","https://openalex.org/W4365211920","https://openalex.org/W2128027845","https://openalex.org/W3014948380","https://openalex.org/W4386184937","https://openalex.org/W4394728283"],"abstract_inverted_index":{"Multi-object":[0],"tracking":[1,50,59],"(MOT)":[2],"and":[3,51,118,136,160,174,185,195],"trajectory":[4,123,158,168,196],"prediction":[5,52],"are":[6],"two":[7,77],"critical":[8],"components":[9],"in":[10,35,99],"modern":[11],"3D":[12,193],"perception":[13],"systems":[14],"that":[15,24,178],"require":[16],"accurate":[17],"modeling":[18],"of":[19,43,48,138,153,165],"multi-agent":[20],"interaction.":[21,45],"We":[22,170],"hypothesize":[23],"it":[25],"is":[26,108,146],"beneficial":[27],"to":[28,37,60,67,95,110,132,148],"unify":[29],"both":[30],"tasks":[31],"under":[32],"one":[33,104],"framework":[34,66,75],"order":[36],"learn":[38],"a":[39,64,85,128,151,156],"shared":[40],"feature":[41,86,113,183],"representation":[42],"agent":[44],"Furthermore,":[46],"instead":[47],"performing":[49],"sequentially":[53],"which":[54,100],"can":[55],"propagate":[56],"errors":[57],"from":[58,155],"prediction,":[61],"we":[62,83,126],"propose":[63],"parallelized":[65],"mitigate":[68],"the":[69,97,134,163],"issue.":[70],"Also,":[71],"our":[72,139,179],"parallel":[73],"track-forecast":[74],"incorporates":[76],"additional":[78],"novel":[79],"computational":[80],"units.":[81],"First,":[82],"use":[84,127],"interaction":[87],"technique":[88],"by":[89],"introducing":[90],"Graph":[91],"Neural":[92],"Networks":[93],"(GNNs)":[94],"capture":[96],"way":[98],"agents":[101],"interact":[102],"with":[103,181],"another.":[105],"The":[106,142],"GNN":[107],"able":[109],"improve":[111,133],"discriminative":[112],"learning":[114,184],"for":[115,122],"MOT":[116,194],"association":[117],"provide":[119],"socially-aware":[120,182],"contexts":[121],"prediction.":[124,197],"Second,":[125],"diversity":[129,137,186],"sampling":[130,144,187],"function":[131,145],"quality":[135],"forecasted":[140],"trajectories.":[141],"learned":[143],"trained":[147],"efficiently":[149],"extract":[150],"variety":[152],"outcomes":[154],"generative":[157],"distribution":[159],"helps":[161],"avoid":[162],"problem":[164],"generating":[166],"duplicate":[167],"samples.":[169],"evaluate":[171],"on":[172,192],"KITTI":[173],"nuScenes":[175],"datasets":[176],"showing":[177],"method":[180],"achieves":[188],"new":[189],"state-of-the-art":[190],"performance":[191],"Project":[198],"website":[199],"is:":[200],"http://www.xinshuoweng.com/projects/PTP.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
