{"id":"https://openalex.org/W6963576518","doi":"https://doi.org/10.21227/d5bg-cb07","title":"Mixed Signals V2X Dataset","display_name":"Mixed Signals V2X Dataset","publication_year":2025,"publication_date":"2025-02-19","ids":{"openalex":"https://openalex.org/W6963576518","doi":"https://doi.org/10.21227/d5bg-cb07"},"language":"en","primary_location":{"id":"doi:10.21227/d5bg-cb07","is_oa":true,"landing_page_url":"https://doi.org/10.21227/d5bg-cb07","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/d5bg-cb07","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Luo, Katie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Katie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Dao, Minh-Quan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dao, Minh-Quan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Liu, Zhenzhen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhenzhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Campbell, Mark","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Campbell, Mark","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Chao, Wei-Lun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chao, Wei-Lun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Weinberger, Kilian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weinberger, Kilian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Malis, Ezio","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Malis, Ezio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Fremont, Vincent","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fremont, Vincent","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Hariharan, Bharath","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hariharan, Bharath","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Shan, Mao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shan, Mao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Worrall, Stewart","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Worrall, Stewart","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Berrio Perez, Julie Stephany","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Berrio Perez, Julie Stephany","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":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.7099999785423279},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6812000274658203},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6175000071525574},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6025000214576721},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5077999830245972},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5058000087738037}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7276999950408936},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.7099999785423279},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6812000274658203},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6175000071525574},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6025000214576721},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5156999826431274},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5077999830245972},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4147000014781952},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31790000200271606},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.272599995136261}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/d5bg-cb07","is_oa":true,"landing_page_url":"https://doi.org/10.21227/d5bg-cb07","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.21227/d5bg-cb07","is_oa":true,"landing_page_url":"https://doi.org/10.21227/d5bg-cb07","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"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":{"Vehicle-to-everything":[0],"(V2X)":[1],"collaborative":[2],"perception":[3,16,87,122],"has":[4],"emerged":[5],"as":[6],"a":[7,36,64],"promising":[8],"solution":[9],"to":[10],"address":[11,29],"the":[12,94,113],"limitations":[13],"of":[14,60,96,112],"single-vehicle":[15],"systems.":[17],"However,":[18],"existing":[19,102],"V2X":[20,38,103,108,121],"datasets":[21,117],"are":[22],"limited":[23],"in":[24],"scope,":[25],"diversity,":[26],"and":[27,44,76,99],"quality. To":[28],"these":[30],"gaps,":[31],"we":[32],"present":[33],"Mixed":[34],"Signals,":[35],"comprehensive":[37],"dataset":[39,70,98],"featuring":[40],"45.1k":[41],"point":[42,74],"clouds":[43,75],"240.6k":[45],"bounding":[46,77],"boxes":[47],"collected":[48],"from":[49],"three":[50],"connected":[51],"autonomous":[52],"vehicles":[53],"(CAVs)":[54],"equipped":[55],"with":[56,67],"two":[57],"different":[58],"types":[59],"LiDAR":[61],"sensors,":[62],"plus":[63],"roadside":[65],"unit":[66],"dual":[68],"LiDARs. Our":[69],"provides":[71],"precisely":[72],"aligned":[73],"box":[78],"annotations":[79],"across":[80],"10":[81],"classes,":[82],"ensuring":[83],"reliable":[84],"data":[85],"for":[86,120],"training. We":[88],"provide":[89],"detailed":[90],"statistical":[91],"analysis":[92],"on":[93,105],"quality":[95],"our":[97],"extensively":[100],"benchmark":[101],"methods":[104],"it. Mixed":[106],"Signals":[107],"Dataset":[109],"is":[110],"one":[111],"highest":[114],"quality,":[115],"large-scale":[116],"publicly":[118],"available":[119],"research:":[123],"https://mixedsignalsdataset.cs.cornell.edu/.":[124]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}