{"id":"https://openalex.org/W4401417297","doi":"https://doi.org/10.1109/icra57147.2024.10611405","title":"LPFormer: LiDAR Pose Estimation Transformer with Multi-Task Network","display_name":"LPFormer: LiDAR Pose Estimation Transformer with Multi-Task Network","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401417297","doi":"https://doi.org/10.1109/icra57147.2024.10611405"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10611405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611405","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/A5039503824","display_name":"Dongqiangzi Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dongqiangzi Ye","raw_affiliation_strings":["TuSimple"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TuSimple","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100958540","display_name":"Yufei Xie","orcid":"https://orcid.org/0009-0005-6992-3852"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yufei Xie","raw_affiliation_strings":["TuSimple"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TuSimple","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100710073","display_name":"Weijia Chen","orcid":"https://orcid.org/0009-0008-6460-1071"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weijia Chen","raw_affiliation_strings":["TuSimple"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TuSimple","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101546895","display_name":"Zixiang Zhou","orcid":"https://orcid.org/0000-0002-4409-2029"},"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":"Zixiang Zhou","raw_affiliation_strings":["University of Central Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066141954","display_name":"Lingting Ge","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lingting Ge","raw_affiliation_strings":["TuSimple"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TuSimple","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076117344","display_name":"Hassan Foroosh","orcid":"https://orcid.org/0000-0002-7601-8165"},"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":"Hassan Foroosh","raw_affiliation_strings":["University of Central Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5791,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.87580545,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"16432","last_page":"16438"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9990000128746033,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9990000128746033,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9966999888420105,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/transformer","display_name":"Transformer","score":0.7014409303665161},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.661842405796051},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.6320260167121887},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5838930606842041},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48021039366722107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4565765857696533},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4224802255630493},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.272187203168869},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12877881526947021},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11630430817604065},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.11291486024856567},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.09020468592643738},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.05082440376281738}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7014409303665161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.661842405796051},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6320260167121887},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5838930606842041},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48021039366722107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4565765857696533},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4224802255630493},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.272187203168869},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12877881526947021},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11630430817604065},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.11291486024856567},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.09020468592643738},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.05082440376281738}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10611405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611405","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":[{"score":0.5899999737739563,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1967554269","https://openalex.org/W2560609797","https://openalex.org/W2916798096","https://openalex.org/W2962962024","https://openalex.org/W2981561950","https://openalex.org/W3034399482","https://openalex.org/W3035172746","https://openalex.org/W3096609285","https://openalex.org/W3167095230","https://openalex.org/W3173283771","https://openalex.org/W4214619583","https://openalex.org/W4226016257","https://openalex.org/W4231018136","https://openalex.org/W4311726826","https://openalex.org/W4312518484","https://openalex.org/W4312967365","https://openalex.org/W4319323473","https://openalex.org/W4382240251","https://openalex.org/W4382466579","https://openalex.org/W4385301217","https://openalex.org/W4401416239","https://openalex.org/W6846964981","https://openalex.org/W6849162881"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4281783339","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W1964041166","https://openalex.org/W4390887692","https://openalex.org/W4210818033"],"abstract_inverted_index":{"Due":[0],"to":[1,115,163],"the":[2,31,38,46,68,99,142,146,151,156],"difficulty":[3],"of":[4,33,40,49,93],"acquiring":[5],"large-scale":[6],"3D":[7,14,50,72,89,127],"human":[8,15,42,73,100,117],"keypoint":[9],"annotation,":[10],"previous":[11,164],"methods":[12],"for":[13,70],"pose":[16,74],"estimation":[17],"(HPE)":[18],"have":[19],"often":[20],"relied":[21],"on":[22,120,150],"2D":[23,28,54],"image":[24],"features":[25,143],"and":[26,45,103,108,139,159],"sequential":[27],"annotations.":[29,90],"Furthermore,":[30],"training":[32],"these":[34,121],"networks":[35],"typically":[36],"assumes":[37],"prediction":[39],"a":[41,112,134],"bounding":[43,101],"box":[44,102],"accurate":[47],"alignment":[48],"point":[51],"clouds":[52],"with":[53,86],"images,":[55],"making":[56],"direct":[57],"application":[58],"in":[59],"real-world":[60],"scenarios":[61],"challenging.":[62],"In":[63],"this":[64],"paper,":[65],"we":[66],"present":[67],"1stframework":[69],"end-to-end":[71],"estimation,":[75],"named":[76],"LPFormer,":[77],"which":[78],"uses":[79],"only":[80],"LiDAR":[81,136],"as":[82],"its":[83,87],"input":[84],"along":[85],"corresponding":[88],"LPFormer":[91],"consists":[92],"two":[94],"stages:":[95],"firstly,":[96],"it":[97,110],"identifies":[98],"extracts":[104],"multi-level":[105],"feature":[106],"representations,":[107],"secondly,":[109],"utilizes":[111],"transformer-based":[113],"network":[114,138],"predict":[116],"keypoints":[118],"based":[119],"features.":[122],"Our":[123],"method":[124],"demonstrates":[125],"that":[126],"HPE":[128],"can":[129],"be":[130],"seamlessly":[131],"integrated":[132],"into":[133],"strong":[135],"perception":[137],"benefit":[140],"from":[141],"extracted":[144],"by":[145],"network.":[147],"Experimental":[148],"results":[149],"Waymo":[152],"Open":[153],"Dataset":[154],"demonstrate":[155],"state-of-the-art":[157],"performance,":[158],"improvements":[160],"even":[161],"compared":[162],"multi-modal":[165],"solutions.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}