{"id":"https://openalex.org/W7138857369","doi":"https://doi.org/10.48550/arxiv.2603.15767","title":"CLRNet: Targetless Extrinsic Calibration for Camera, Lidar and 4D Radar Using Deep Learning","display_name":"CLRNet: Targetless Extrinsic Calibration for Camera, Lidar and 4D Radar Using Deep Learning","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7138857369","doi":"https://doi.org/10.48550/arxiv.2603.15767"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.15767","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15767","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.15767","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130151590","display_name":"Marcell Kegl","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kegl, Marcell","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066202708","display_name":"Andras Palffy","orcid":"https://orcid.org/0000-0003-1663-4967"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Palffy, Andras","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044638075","display_name":"Csaba Benedek","orcid":"https://orcid.org/0000-0003-3203-0741"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Benedek, Csaba","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085298812","display_name":"Dariu M. Gavrila","orcid":"https://orcid.org/0000-0002-1810-4196"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gavrila, Dariu M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.4311999976634979,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.4311999976634979,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.3319999873638153,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.060100000351667404,"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/calibration","display_name":"Calibration","score":0.7867000102996826},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.646399974822998},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5830000042915344},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5490000247955322},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5418999791145325},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.44859999418258667},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44279998540878296},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.37959998846054077}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7867000102996826},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6657000184059143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6559000015258789},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.646399974822998},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6417999863624573},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5830000042915344},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5490000247955322},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5418999791145325},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4542999863624573},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44279998540878296},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.37770000100135803},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.272599995136261},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.26739999651908875},{"id":"https://openalex.org/C134406370","wikidata":"https://www.wikidata.org/wiki/Q832005","display_name":"Radar engineering details","level":4,"score":0.2648000121116638},{"id":"https://openalex.org/C81076408","wikidata":"https://www.wikidata.org/wiki/Q229387","display_name":"3D radar","level":5,"score":0.2621000111103058},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.15767","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15767","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.15767","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15767","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,79],"this":[1],"paper,":[2],"we":[3,88,111],"address":[4],"extrinsic":[5,15],"calibration":[6,16,39,49,91,104],"for":[7],"camera,":[8],"lidar,":[9],"and":[10,67,75,85,102,121],"4D":[11],"radar":[12,18,65],"sensors.":[13,55],"Accurate":[14],"of":[17,26,42,53,117],"remains":[19],"a":[20,32,71],"challenge":[21],"due":[22],"to":[23,94],"the":[24,83,113,118],"sparsity":[25],"its":[27],"data.":[28],"We":[29,56],"propose":[30],"CLRNet,":[31],"novel,":[33],"multi-modal":[34],"end-to-end":[35],"deep":[36],"learning":[37],"(DL)":[38],"network":[40,120],"capable":[41],"addressing":[43],"joint":[44],"camera-lidar-radar":[45],"calibration,":[46],"or":[47],"pairwise":[48],"between":[50],"any":[51],"two":[52],"these":[54],"incorporate":[57],"equirectangular":[58],"projection,":[59],"camera-based":[60],"depth":[61],"image":[62],"prediction,":[63],"additional":[64],"channels,":[66],"leverage":[68],"lidar":[69],"with":[70],"shared":[72],"feature":[73],"space":[74],"loop":[76],"closure":[77],"loss.":[78],"extensive":[80],"experiments":[81],"using":[82],"View-of-Delft":[84],"Dual-Radar":[86],"datasets,":[87],"demonstrate":[89],"superior":[90],"accuracy":[92],"compared":[93],"existing":[95],"state-of-the-art":[96],"methods,":[97],"reducing":[98],"both":[99],"median":[100],"translational":[101],"rotational":[103],"errors":[105],"by":[106],"at":[107],"least":[108],"50%.":[109],"Finally,":[110],"examine":[112],"domain":[114],"transfer":[115],"capabilities":[116],"proposed":[119],"baselines,":[122],"when":[123],"evaluating":[124],"across":[125],"datasets.":[126],"The":[127],"code":[128],"will":[129],"be":[130],"made":[131],"publicly":[132],"available":[133],"upon":[134],"acceptance":[135],"at:":[136],"https://github.com/tudelft-iv.":[137]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-20T00:00:00"}
