{"id":"https://openalex.org/W4383108963","doi":"https://doi.org/10.1109/icra48891.2023.10160305","title":"3DMODT: Attention-Guided Affinities for Joint Detection & Tracking in 3D Point Clouds","display_name":"3DMODT: Attention-Guided Affinities for Joint Detection & Tracking in 3D Point Clouds","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383108963","doi":"https://doi.org/10.1109/icra48891.2023.10160305"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 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/A5069416535","display_name":"Jyoti Kini","orcid":"https://orcid.org/0000-0002-3351-9517"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jyoti Kini","raw_affiliation_strings":["University of Central Florida,Center for Research in Computer Vision,USA","Center for Research in Computer Vision, University of Central Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida,Center for Research in Computer Vision,USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Center for Research in Computer Vision, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089986388","display_name":"Ajmal Mian","orcid":"https://orcid.org/0000-0002-5206-3842"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"The University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ajmal Mian","raw_affiliation_strings":["University of Western,Australia","University of Western, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Western,Australia","institution_ids":["https://openalex.org/I177877127"]},{"raw_affiliation_string":"University of Western, Australia","institution_ids":["https://openalex.org/I177877127"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080823547","display_name":"Mubarak Shah","orcid":"https://orcid.org/0000-0001-6172-5572"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mubarak Shah","raw_affiliation_strings":["University of Central Florida,Center for Research in Computer Vision,USA","Center for Research in Computer Vision, University of Central Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida,Center for Research in Computer Vision,USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Center for Research in Computer Vision, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"841","last_page":"848"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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":0.9991000294685364,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7531841397285461},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7263833284378052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6341681480407715},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5819749236106873},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5780856013298035},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5677568912506104},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5669186115264893},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4687481224536896},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4572065472602844},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43893152475357056},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4224545955657959},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4175838828086853},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4007626473903656},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1558946669101715}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7531841397285461},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7263833284378052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6341681480407715},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5819749236106873},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5780856013298035},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5677568912506104},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5669186115264893},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4687481224536896},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4572065472602844},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43893152475357056},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4224545955657959},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4175838828086853},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4007626473903656},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1558946669101715},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra48891.2023.10160305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/8df2b186-c27d-4f3b-8dd3-ca0345ba6c48","is_oa":false,"landing_page_url":"https://research-repository.uwa.edu.au/en/publications/8df2b186-c27d-4f3b-8dd3-ca0345ba6c48","pdf_url":null,"source":{"id":"https://openalex.org/S4306402492","display_name":"UWA Profiles and Research Repository (UWA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177877127","host_organization_name":"The University of Western Australia","host_organization_lineage":["https://openalex.org/I177877127"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kini, J, Mian, A & Shah, M 2023, 3DMODT : Attention-Guided Affinities for Joint Detection & Tracking in 3D Point Clouds. in Proceedings - ICRA 2023 : IEEE International Conference on Robotics and Automation. Proceedings - IEEE International Conference on Robotics and Automation, vol. 2023-May, IEEE, Institute of Electrical and Electronics Engineers, pp. 841-848, 2023 IEEE International Conference on Robotics and Automation, London, United Kingdom, 29/05/23. https://doi.org/10.1109/ICRA48891.2023.10160305","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8222488688","display_name":"Robust and Explainable 3D Computer Vision","funder_award_id":"FT210100268","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W2105934661","https://openalex.org/W2150066425","https://openalex.org/W2603203130","https://openalex.org/W2766459852","https://openalex.org/W2897529137","https://openalex.org/W2951517617","https://openalex.org/W2953106684","https://openalex.org/W2963049565","https://openalex.org/W2963091558","https://openalex.org/W2963727135","https://openalex.org/W2968296999","https://openalex.org/W2971306974","https://openalex.org/W2983227562","https://openalex.org/W2990613095","https://openalex.org/W3003256722","https://openalex.org/W3003533476","https://openalex.org/W3011379053","https://openalex.org/W3034782805","https://openalex.org/W3035172746","https://openalex.org/W3035410385","https://openalex.org/W3035725370","https://openalex.org/W3084173793","https://openalex.org/W3095753995","https://openalex.org/W3096068180","https://openalex.org/W3106763294","https://openalex.org/W3107730255","https://openalex.org/W3107819843","https://openalex.org/W3108381568","https://openalex.org/W3111535274","https://openalex.org/W3115390238","https://openalex.org/W3117804044","https://openalex.org/W3119686997","https://openalex.org/W3130463448","https://openalex.org/W3131716792","https://openalex.org/W3132607695","https://openalex.org/W3133352551","https://openalex.org/W3153465022","https://openalex.org/W3167095230","https://openalex.org/W3167949052","https://openalex.org/W3188754867","https://openalex.org/W3190141195","https://openalex.org/W3196204376","https://openalex.org/W3207452968","https://openalex.org/W3207707490","https://openalex.org/W4214612132","https://openalex.org/W4214755140","https://openalex.org/W4283795368","https://openalex.org/W4285284118","https://openalex.org/W4312274649","https://openalex.org/W4312473433","https://openalex.org/W4312532041","https://openalex.org/W4312950653","https://openalex.org/W6620707391","https://openalex.org/W6754918364","https://openalex.org/W6773319185","https://openalex.org/W6775038574","https://openalex.org/W6775668235","https://openalex.org/W6781017932","https://openalex.org/W6781711900","https://openalex.org/W6786280728","https://openalex.org/W6788023325","https://openalex.org/W6795368335"],"related_works":["https://openalex.org/W2542007731","https://openalex.org/W4285271403","https://openalex.org/W2968379562","https://openalex.org/W3156013036","https://openalex.org/W4388689193","https://openalex.org/W2892070025","https://openalex.org/W29633852","https://openalex.org/W2091015105","https://openalex.org/W2985362983","https://openalex.org/W2110899030"],"abstract_inverted_index":{"We":[0,95,158],"propose":[1,96],"a":[2,16,21,37,64,70,132],"method":[3,32,164],"for":[4,73],"joint":[5],"detection":[6,26],"and":[7,60,129,148,171],"tracking":[8,156,167],"of":[9,92,134,162,178],"multiple":[10,55],"objects":[11,59],"in":[12,63,119],"3D":[13],"point":[14,85],"clouds,":[15],"task":[17],"conventionally":[18],"treated":[19],"as":[20],"two-step":[22],"process":[23],"comprising":[24],"object":[25,47],"followed":[27],"by":[28,79,106,122],"data":[29],"association.":[30],"Our":[31,49],"embeds":[33],"both":[34],"steps":[35],"into":[36],"single":[38,65],"end-to-end":[39],"trainable":[40],"network":[41,141],"eliminating":[42],"the":[43,103,116,160,176],"dependency":[44],"on":[45,165],"external":[46],"detectors.":[48],"model":[50,180],"exploits":[51],"temporal":[52],"information":[53],"employing":[54,80,123],"frames":[56,153],"to":[57,101,114,154,181],"detect":[58],"track":[61],"them":[62],"network,":[66],"thereby":[67],"making":[68],"it":[69],"utilitarian":[71],"formulation":[72],"real-world":[74],"scenarios.":[75],"Computing":[76],"affinity":[77,104,120,127,135],"matrix":[78,105,121,128],"features":[81],"similarity":[82],"across":[83,131,184],"consecutive":[84],"cloud":[86],"scans":[87],"forms":[88],"an":[89,97],"integral":[90],"part":[91],"visual":[93],"tracking.":[94],"attention-based":[98],"refinement":[99],"module":[100,111],"refine":[102],"suppressing":[107],"erroneous":[108],"correspondences.":[109],"The":[110],"is":[112],"designed":[113],"capture":[115],"global":[117],"context":[118],"self-attention":[124],"within":[125],"each":[126],"cross-attention":[130],"pair":[133],"matrices.":[136],"Unlike":[137],"competing":[138],"approaches,":[139],"our":[140,163,179],"does":[142],"not":[143],"require":[144],"complex":[145],"post-processing":[146],"algorithms,":[147],"directly":[149],"processes":[150],"raw":[151],"LiDAR":[152],"output":[155],"results.":[157],"demonstrate":[159],"effectiveness":[161],"three":[166],"benchmarks:":[168],"JRDB,":[169],"Waymo,":[170],"KITTI.":[172],"Experimental":[173],"evaluations":[174],"indicate":[175],"ability":[177],"generalize":[182],"well":[183],"datasets.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}