{"id":"https://openalex.org/W4401413823","doi":"https://doi.org/10.1109/icra57147.2024.10610591","title":"Breaking Data Silos: Cross-Domain Learning for Multi-Agent Perception from Independent Private Sources","display_name":"Breaking Data Silos: Cross-Domain Learning for Multi-Agent Perception from Independent Private Sources","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401413823","doi":"https://doi.org/10.1109/icra57147.2024.10610591"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10610591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10610591","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":"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/A5100454985","display_name":"Jinlong Li","orcid":"https://orcid.org/0000-0002-8746-4566"},"institutions":[{"id":"https://openalex.org/I102607778","display_name":"Cleveland State University","ror":"https://ror.org/002tx1f22","country_code":"US","type":"education","lineage":["https://openalex.org/I102607778"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jinlong Li","raw_affiliation_strings":["Cleveland State University,Cleveland Vision &amp; AI Lab"],"affiliations":[{"raw_affiliation_string":"Cleveland State University,Cleveland Vision &amp; AI Lab","institution_ids":["https://openalex.org/I102607778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008481358","display_name":"Baolu Li","orcid":"https://orcid.org/0009-0002-4741-8626"},"institutions":[{"id":"https://openalex.org/I102607778","display_name":"Cleveland State University","ror":"https://ror.org/002tx1f22","country_code":"US","type":"education","lineage":["https://openalex.org/I102607778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baolu Li","raw_affiliation_strings":["Cleveland State University,Cleveland Vision &amp; AI Lab"],"affiliations":[{"raw_affiliation_string":"Cleveland State University,Cleveland Vision &amp; AI Lab","institution_ids":["https://openalex.org/I102607778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100581462","display_name":"Xinyu Liu","orcid":"https://orcid.org/0009-0007-4170-6156"},"institutions":[{"id":"https://openalex.org/I102607778","display_name":"Cleveland State University","ror":"https://ror.org/002tx1f22","country_code":"US","type":"education","lineage":["https://openalex.org/I102607778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyu Liu","raw_affiliation_strings":["Cleveland State University,Cleveland Vision &amp; AI Lab"],"affiliations":[{"raw_affiliation_string":"Cleveland State University,Cleveland Vision &amp; AI Lab","institution_ids":["https://openalex.org/I102607778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100700826","display_name":"Runsheng Xu","orcid":"https://orcid.org/0000-0001-7375-9833"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Runsheng Xu","raw_affiliation_strings":["University of California, Los Angeles,UCLA Mobility Lab"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles,UCLA Mobility Lab","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068374815","display_name":"Jiaqi Ma","orcid":"https://orcid.org/0000-0002-8184-5157"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaqi Ma","raw_affiliation_strings":["University of California, Los Angeles,UCLA Mobility Lab"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles,UCLA Mobility Lab","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025512337","display_name":"Hongkai Yu","orcid":"https://orcid.org/0000-0001-5383-8913"},"institutions":[{"id":"https://openalex.org/I102607778","display_name":"Cleveland State University","ror":"https://ror.org/002tx1f22","country_code":"US","type":"education","lineage":["https://openalex.org/I102607778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongkai Yu","raw_affiliation_strings":["Cleveland State University,Cleveland Vision &amp; AI Lab"],"affiliations":[{"raw_affiliation_string":"Cleveland State University,Cleveland Vision &amp; AI Lab","institution_ids":["https://openalex.org/I102607778"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100454985"],"corresponding_institution_ids":["https://openalex.org/I102607778"],"apc_list":null,"apc_paid":null,"fwci":2.1822,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.89187041,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"18414","last_page":"18420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/information-silo","display_name":"Information silo","score":0.781107485294342},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5681242942810059},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5518006086349487},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.42553412914276123},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15273287892341614},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11088359355926514}],"concepts":[{"id":"https://openalex.org/C48255552","wikidata":"https://www.wikidata.org/wiki/Q6031230","display_name":"Information silo","level":3,"score":0.781107485294342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5681242942810059},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5518006086349487},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.42553412914276123},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15273287892341614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11088359355926514},{"id":"https://openalex.org/C2778024958","wikidata":"https://www.wikidata.org/wiki/Q213643","display_name":"Silo","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"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/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10610591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10610591","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2340897893","https://openalex.org/W2912213068","https://openalex.org/W2963200935","https://openalex.org/W2963351448","https://openalex.org/W2963819344","https://openalex.org/W2968296999","https://openalex.org/W2985739927","https://openalex.org/W3109991383","https://openalex.org/W3201193904","https://openalex.org/W4286544732","https://openalex.org/W4297411803","https://openalex.org/W4312604822","https://openalex.org/W4312939270","https://openalex.org/W4321609084","https://openalex.org/W4352977781","https://openalex.org/W4383108477","https://openalex.org/W4383108819","https://openalex.org/W4383220221","https://openalex.org/W4386066469","https://openalex.org/W4386071537","https://openalex.org/W4386076547","https://openalex.org/W4390873301","https://openalex.org/W4390874305","https://openalex.org/W6688325169","https://openalex.org/W6728757088","https://openalex.org/W6745935785","https://openalex.org/W6757817989","https://openalex.org/W6785667878","https://openalex.org/W6839180059","https://openalex.org/W6842774165"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2362191124","https://openalex.org/W2199380551","https://openalex.org/W2551780525","https://openalex.org/W2015682392","https://openalex.org/W2379482292","https://openalex.org/W2378996641","https://openalex.org/W2042575934","https://openalex.org/W1977446600"],"abstract_inverted_index":{"The":[0,60,177],"diverse":[1],"agents":[2,35,55],"in":[3,40,56,70,75,117,160],"multi-agent":[4,57,76,92,118,146,174],"perception":[5,58,93,175],"systems":[6],"may":[7],"be":[8],"from":[9],"different":[10,49],"companies.":[11],"Each":[12],"company":[13],"might":[14],"use":[15],"the":[16,28,33,45,64,84,87,97,102,113,142,151],"identical":[17],"classic":[18],"neural":[19],"network":[20],"architecture":[21],"based":[22],"encoder":[23],"for":[24,52,108],"feature":[25],"extraction.":[26],"However,":[27],"data":[29,51,61,98],"source":[30],"to":[31,44,111,140,172],"train":[32],"various":[34],"is":[36,179],"independent":[37],"and":[38,129,154],"private":[39,50],"each":[41],"company,":[42],"leading":[43],"Distribution":[46,66,115],"Gap":[47,67,116],"of":[48,86],"training":[53],"distinct":[54],"system.":[59],"silos":[62],"by":[63],"above":[65,114],"could":[68],"result":[69],"a":[71],"significant":[72],"performance":[73],"decline":[74],"perception.":[77,119],"In":[78],"this":[79],"paper,":[80],"we":[81,100],"thoroughly":[82],"examine":[83],"impact":[85],"distribution":[88,143],"gap":[89,144],"on":[90,150],"existing":[91,173],"systems.":[94,176],"To":[95],"break":[96],"silos,":[99],"introduce":[101],"Feature":[103,126],"Distribution-aware":[104,130],"Aggregation":[105],"(FDA)":[106],"framework":[107],"cross-domain":[109],"learning":[110],"mitigate":[112],"FDA":[120],"comprises":[121],"two":[122],"key":[123],"components:":[124],"Learnable":[125],"Compensation":[127],"Module":[128],"Statistical":[131],"Consistency":[132],"Module,":[133],"both":[134],"aimed":[135],"at":[136,181],"enhancing":[137],"intermediate":[138],"features":[139],"minimize":[141],"among":[145],"features.":[147],"Intensive":[148],"experiments":[149],"public":[152],"OPV2V":[153],"V2XSet":[155],"datasets":[156],"underscore":[157],"FDA\u2019s":[158],"effectiveness":[159],"point":[161],"cloud-based":[162],"3D":[163],"object":[164],"detection,":[165],"presenting":[166],"it":[167],"as":[168],"an":[169],"invaluable":[170],"augmentation":[171],"code":[178],"available":[180],"https://github.com/jinlong17/BDS-V2V.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
