{"id":"https://openalex.org/W4408353760","doi":"https://doi.org/10.1109/icassp49660.2025.10887630","title":"RelaI2P: Relational Learning for Image-to-Point Cloud Registration","display_name":"RelaI2P: Relational Learning for Image-to-Point Cloud Registration","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408353760","doi":"https://doi.org/10.1109/icassp49660.2025.10887630"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10887630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10887630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5112661776","display_name":"Minghui Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210134929","display_name":"Jilin Province Science and Technology Department","ror":"https://ror.org/049x38272","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134929"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghui Hou","raw_affiliation_strings":["Jilin University,College of Computer Science and Technology,Changchun,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin University,College of Computer Science and Technology,Changchun,China","institution_ids":["https://openalex.org/I4210134929","https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210134929","display_name":"Jilin Province Science and Technology Department","ror":"https://ror.org/049x38272","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134929"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Wang","raw_affiliation_strings":["Jilin University,College of Computer Science and Technology,Changchun,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin University,College of Computer Science and Technology,Changchun,China","institution_ids":["https://openalex.org/I4210134929","https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100710658","display_name":"Zhiyang Wang","orcid":"https://orcid.org/0000-0003-0908-4442"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyang Wang","raw_affiliation_strings":["Jilin University,College of Software,Changchun,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin University,College of Software,Changchun,China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034970671","display_name":"Baorui Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baorui Ma","raw_affiliation_strings":["Beijing Academy of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Academy of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2684,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7657063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9539999961853027,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.949400007724762,"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/computer-science","display_name":"Computer science","score":0.6879699230194092},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6471335887908936},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6408722400665283},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4995536804199219},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.438012957572937},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.4376981556415558},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41529732942581177},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.04650384187698364}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6879699230194092},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6471335887908936},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6408722400665283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4995536804199219},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.438012957572937},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.4376981556415558},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41529732942581177},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.04650384187698364}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10887630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10887630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335953","display_name":"Jilin Scientific and Technological Development Program","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1991544872","https://openalex.org/W2115579991","https://openalex.org/W2194775991","https://openalex.org/W2320444803","https://openalex.org/W2752782242","https://openalex.org/W2897529137","https://openalex.org/W2908599206","https://openalex.org/W2963132934","https://openalex.org/W2963270286","https://openalex.org/W2967098543","https://openalex.org/W2979458572","https://openalex.org/W2981556384","https://openalex.org/W3034552520","https://openalex.org/W3034675048","https://openalex.org/W3170994844","https://openalex.org/W4205399869","https://openalex.org/W4224434530","https://openalex.org/W4296913583","https://openalex.org/W4312950511","https://openalex.org/W4313176116","https://openalex.org/W4372265771","https://openalex.org/W4382466543","https://openalex.org/W4383066393","https://openalex.org/W4392902904","https://openalex.org/W4392904317","https://openalex.org/W6739778489","https://openalex.org/W6796277869","https://openalex.org/W6853442197","https://openalex.org/W6857525286","https://openalex.org/W6859295814"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W3150465815","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W2802581102","https://openalex.org/W4205786897"],"abstract_inverted_index":{"Cross-modality":[0],"registration":[1],"between":[2,23,63,86,105,121],"2D":[3],"images":[4,24,111],"and":[5,16,25,33,50,65,88,112,144],"3D":[6],"point":[7,26,34,66,113],"clouds":[8,27],"is":[9,80],"an":[10],"important":[11],"task":[12],"in":[13,47],"autonomous":[14],"driving":[15],"robotics.":[17],"Existing":[18],"methods":[19],"predict":[20],"the":[21,44,53,84,103,122,128,156],"correspondence":[22,85],"by":[28,37],"matching":[29],"patterns":[30],"of":[31,73,108],"pixel":[32],"features":[35,109,143],"learned":[36],"deep":[38],"neural":[39],"networks.":[40],"However,":[41],"due":[42],"to":[43,70,127],"significant":[45],"differences":[46],"their":[48,145],"representation":[49],"feature":[51,54,61,123],"processing,":[52],"spaces":[55],"are":[56],"vastly":[57],"different.":[58],"The":[59,147,159],"insufficient":[60],"interaction":[62],"image":[64],"cloud":[67],"branches":[68,125],"leads":[69],"a":[71,96,134],"lack":[72],"information":[74,119],"necessary":[75],"for":[76,82],"relational":[77],"reasoning,":[78],"which":[79],"crucial":[81],"establishing":[83],"pixels":[87],"points.":[89],"To":[90],"address":[91],"these":[92],"problems,":[93],"we":[94,132],"propose":[95],"Cross-Modality":[97],"Relation":[98],"Module":[99,137],"(CMRM)":[100],"that":[101,139],"leverages":[102],"relations":[104],"different":[106],"levels":[107],"from":[110],"clouds.":[114],"This":[115],"module":[116],"facilitates":[117],"rich":[118],"exchange":[120],"extractor":[124],"corresponding":[126],"two":[129],"modalities.":[130],"Additionally,":[131],"introduce":[133],"Relation-Aware":[135],"Fusion":[136],"(RAFM)":[138],"effectively":[140],"integrates":[141],"multimodal":[142],"relations.":[146],"experimental":[148],"results":[149],"on":[150],"KITTI":[151],"dataset":[152],"show":[153],"improvements":[154],"over":[155],"state-of-the-art":[157],"methods.":[158],"code":[160],"will":[161],"be":[162],"publicly":[163],"available":[164],"at":[165],"https://github.com/JLUrob/RelaI2P.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-04T07:58:01.006859","created_date":"2025-10-10T00:00:00"}
