{"id":"https://openalex.org/W4407948433","doi":"https://doi.org/10.1109/tits.2025.3538765","title":"Unsupervised Learning of 3D Scene Flow With LiDAR Odometry Assistance","display_name":"Unsupervised Learning of 3D Scene Flow With LiDAR Odometry Assistance","publication_year":2025,"publication_date":"2025-02-26","ids":{"openalex":"https://openalex.org/W4407948433","doi":"https://doi.org/10.1109/tits.2025.3538765"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3538765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3538765","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","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/A5100336735","display_name":"Guangming Wang","orcid":"https://orcid.org/0000-0002-7675-543X"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Guangming Wang","raw_affiliation_strings":["Department of Engineering, University of Cambridge, Cambridge, U.K"],"raw_orcid":"https://orcid.org/0000-0002-7675-543X","affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Cambridge, Cambridge, U.K","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041847755","display_name":"Zhiheng Feng","orcid":"https://orcid.org/0000-0001-8014-6410"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Feng","raw_affiliation_strings":["Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8014-6410","affiliations":[{"raw_affiliation_string":"Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035461693","display_name":"Chaokang Jiang","orcid":"https://orcid.org/0000-0002-3504-843X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaokang Jiang","raw_affiliation_strings":["PhiGent Robotics, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3504-843X","affiliations":[{"raw_affiliation_string":"PhiGent Robotics, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045252539","display_name":"Jiuming Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiuming Liu","raw_affiliation_strings":["Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0001-8047-3814","affiliations":[{"raw_affiliation_string":"Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107772128","display_name":"Hesheng Wang","orcid":"https://orcid.org/0000-0002-9959-1634"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hesheng Wang","raw_affiliation_strings":["Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9959-1634","affiliations":[{"raw_affiliation_string":"Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100336735"],"corresponding_institution_ids":["https://openalex.org/I241749"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02878517,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"4","first_page":"4557","last_page":"4567"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10577","display_name":"Hydrology and Sediment Transport Processes","score":0.8996999859809875,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10577","display_name":"Hydrology and Sediment Transport Processes","score":0.8996999859809875,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.8952999711036682,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.8747000098228455,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8098585605621338},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.751606822013855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6626257300376892},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5878351926803589},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.57257080078125},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4205428957939148},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.283827543258667},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.22110649943351746},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.16240271925926208},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10881602764129639},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.09108972549438477}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8098585605621338},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.751606822013855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6626257300376892},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5878351926803589},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.57257080078125},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4205428957939148},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.283827543258667},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.22110649943351746},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.16240271925926208},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10881602764129639},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.09108972549438477}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3538765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3538765","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1545384812","display_name":null,"funder_award_id":"62225309","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5163237521","display_name":null,"funder_award_id":"U21A20480","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5381884387","display_name":null,"funder_award_id":"U24A20278","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6990729683","display_name":null,"funder_award_id":"62361166632","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2049981393","https://openalex.org/W2115579991","https://openalex.org/W2129671742","https://openalex.org/W2134236847","https://openalex.org/W2150066425","https://openalex.org/W2157364932","https://openalex.org/W2259424905","https://openalex.org/W2286655030","https://openalex.org/W2519911873","https://openalex.org/W2770902190","https://openalex.org/W2779333428","https://openalex.org/W2962771259","https://openalex.org/W2966072084","https://openalex.org/W2971686478","https://openalex.org/W2983104849","https://openalex.org/W3008681115","https://openalex.org/W3034321406","https://openalex.org/W3092856933","https://openalex.org/W3097139398","https://openalex.org/W3106932526","https://openalex.org/W3127986322","https://openalex.org/W3128818397","https://openalex.org/W3166975282","https://openalex.org/W3167610791","https://openalex.org/W3201334943","https://openalex.org/W3206941470","https://openalex.org/W3209906369","https://openalex.org/W4226137188","https://openalex.org/W4226322709","https://openalex.org/W4312253406","https://openalex.org/W4312472981","https://openalex.org/W4312603966","https://openalex.org/W4377971342","https://openalex.org/W4382459110","https://openalex.org/W4386075670","https://openalex.org/W4394593007","https://openalex.org/W6631190155","https://openalex.org/W6739778489","https://openalex.org/W6852907373"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"3D":[0,5,18,44,65,160],"scene":[1,66,118,128,140,161,189,232],"flow":[2,26,67,119,129,141,190,233],"represents":[3],"the":[4,11,61,73,83,127,156,175,188,203,226,230,245],"motion":[6,81],"of":[7,64,75,78,85,117,159,205,248],"each":[8,88],"point":[9,12,89],"in":[10,42,90,218],"cloud,":[13],"which":[14,54,102,125],"is":[15,68,95,123,212],"a":[16,112,149,192,208,219],"base":[17],"perception":[19],"task":[20],"for":[21,27,155,173,186],"autonomous":[22],"driving,":[23],"like":[24],"optical":[25],"2D":[28],"images.":[29],"As":[30],"non-learning":[31],"methods":[32,242],"are":[33,170,183,199,258],"often":[34],"inefficient":[35],"or":[36],"struggled":[37],"to":[38,50,72,97,99,201,214,240,252],"learn":[39],"accurate":[40,151],"correspondence":[41],"complex":[43],"real":[45],"world,":[46],"recent":[47],"works":[48],"turn":[49],"supervised":[51,146],"learning":[52,115],"methods,":[53,101],"require":[55,105],"ground":[56,62,106],"truth":[57,63,107],"labels.":[58,108,142],"However,":[59],"acquiring":[60],"challenging":[69],"mainly":[70],"due":[71],"lack":[74],"sensors":[76],"capable":[77],"capturing":[79],"point-level":[80],"and":[82,167,180,195,207],"complexity":[84],"accurately":[86],"tracking":[87],"real-world":[91,136,253],"environments.":[92],"Therefore,":[93],"it":[94],"important":[96],"resort":[98],"self-supervised":[100],"do":[103],"not":[104],"In":[109,143,163],"this":[110,144],"paper,":[111],"novel":[113],"unsupervised":[114],"method":[116,251],"with":[120],"LiDAR":[121,137],"odometry":[122,147],"proposed,":[124],"enables":[126],"network":[130],"can":[131],"be":[132],"trained":[133],"directly":[134],"on":[135],"data":[138],"without":[139],"structure,":[145],"provides":[148],"more":[150,171,184,234],"shared":[152],"cost":[153],"volume":[154],"interframe":[157],"association":[158],"flow.":[162],"addition,":[164],"because":[165],"static":[166,193],"occluded":[168],"points":[169,182,206,217],"suitable":[172,185],"using":[174,187],"pose":[176],"transform":[177,215],"while":[178],"dynamic":[179],"non-occluded":[181],"transform,":[191],"mask":[194,198],"an":[196],"occlusion":[197],"designed":[200],"classify":[202],"states":[204],"mask-weighted":[209],"warp":[210],"layer":[211],"proposed":[213,250],"source":[216,256],"divide-and-conquer":[220,227],"manner.":[221],"The":[222,236],"experiments":[223],"demonstrate":[224],"that":[225],"strategy":[228],"makes":[229],"predicted":[231],"accurate.":[235],"experiment":[237],"results":[238],"compared":[239],"other":[241],"also":[243],"show":[244],"application":[246],"ability":[247],"our":[249],"data.":[254],"Our":[255],"codes":[257],"released":[259],"at:":[260],"<uri":[261],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[262],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/IRMVLab/PSFNet</uri>.":[263]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
