{"id":"https://openalex.org/W4401415956","doi":"https://doi.org/10.1109/icra57147.2024.10610015","title":"Orientation-Aware Multi-Modal Learning for Road Intersection Identification and Mapping","display_name":"Orientation-Aware Multi-Modal Learning for Road Intersection Identification and Mapping","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401415956","doi":"https://doi.org/10.1109/icra57147.2024.10610015"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10610015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10610015","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/A5032046883","display_name":"Qibin He","orcid":"https://orcid.org/0000-0003-2158-559X"},"institutions":[{"id":"https://openalex.org/I4401726823","display_name":"Nio (China)","ror":"https://ror.org/02w12zj89","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726823"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qibin He","raw_affiliation_strings":["NIO Inc.,Autonomous Driving Division,Beijing,China"],"affiliations":[{"raw_affiliation_string":"NIO Inc.,Autonomous Driving Division,Beijing,China","institution_ids":["https://openalex.org/I4401726823"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019559756","display_name":"Zhongyang Xiao","orcid":"https://orcid.org/0000-0003-0571-9156"},"institutions":[{"id":"https://openalex.org/I4401726823","display_name":"Nio (China)","ror":"https://ror.org/02w12zj89","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726823"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyang Xiao","raw_affiliation_strings":["NIO Inc.,Autonomous Driving Division,Beijing,China"],"affiliations":[{"raw_affiliation_string":"NIO Inc.,Autonomous Driving Division,Beijing,China","institution_ids":["https://openalex.org/I4401726823"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023283504","display_name":"Qiulin Huang","orcid":"https://orcid.org/0000-0001-5667-626X"},"institutions":[{"id":"https://openalex.org/I4401726823","display_name":"Nio (China)","ror":"https://ror.org/02w12zj89","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726823"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ze Huang","raw_affiliation_strings":["NIO Inc.,Autonomous Driving Division,Beijing,China"],"affiliations":[{"raw_affiliation_string":"NIO Inc.,Autonomous Driving Division,Beijing,China","institution_ids":["https://openalex.org/I4401726823"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106746217","display_name":"Hongyuan Yuan","orcid":"https://orcid.org/0000-0003-1913-4829"},"institutions":[{"id":"https://openalex.org/I4401726823","display_name":"Nio (China)","ror":"https://ror.org/02w12zj89","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726823"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyuan Yuan","raw_affiliation_strings":["NIO Inc.,Autonomous Driving Division,Beijing,China"],"affiliations":[{"raw_affiliation_string":"NIO Inc.,Autonomous Driving Division,Beijing,China","institution_ids":["https://openalex.org/I4401726823"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113843738","display_name":"Li Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4401726823","display_name":"Nio (China)","ror":"https://ror.org/02w12zj89","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726823"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Sun","raw_affiliation_strings":["NIO Inc.,Autonomous Driving Division,Beijing,China"],"affiliations":[{"raw_affiliation_string":"NIO Inc.,Autonomous Driving Division,Beijing,China","institution_ids":["https://openalex.org/I4401726823"]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032046883"],"corresponding_institution_ids":["https://openalex.org/I4401726823"],"apc_list":null,"apc_paid":null,"fwci":0.7108,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68563626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"16185","last_page":"16191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9901999831199646,"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/intersection","display_name":"Intersection (aeronautics)","score":0.8011115193367004},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.7390792369842529},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6737463474273682},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6307613253593445},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.629056990146637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5211465358734131},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4591353237628937},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.19855481386184692},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16118183732032776},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.14411967992782593},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11705812811851501},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.06377720832824707}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.8011115193367004},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7390792369842529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6737463474273682},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6307613253593445},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.629056990146637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5211465358734131},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4591353237628937},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.19855481386184692},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16118183732032776},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.14411967992782593},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11705812811851501},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.06377720832824707},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10610015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10610015","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":[{"score":0.5099999904632568,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1989750313","https://openalex.org/W2031489346","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2221280282","https://openalex.org/W2565639579","https://openalex.org/W2725897987","https://openalex.org/W2790715140","https://openalex.org/W2899848438","https://openalex.org/W2908510526","https://openalex.org/W2945911216","https://openalex.org/W2963351448","https://openalex.org/W2964979676","https://openalex.org/W2967975754","https://openalex.org/W2988088449","https://openalex.org/W2988990098","https://openalex.org/W2991566686","https://openalex.org/W2995122008","https://openalex.org/W3015072278","https://openalex.org/W3098839753","https://openalex.org/W3121776973","https://openalex.org/W3135793940","https://openalex.org/W3136761610","https://openalex.org/W3138516171","https://openalex.org/W3173658130","https://openalex.org/W3206393477","https://openalex.org/W3206551498","https://openalex.org/W4214648418","https://openalex.org/W4221145217","https://openalex.org/W4283789390","https://openalex.org/W4296104994","https://openalex.org/W4306362451","https://openalex.org/W4312443924","https://openalex.org/W4312891659","https://openalex.org/W4313026523","https://openalex.org/W4313142062","https://openalex.org/W4320002812","https://openalex.org/W4383066393","https://openalex.org/W4383108615","https://openalex.org/W4386057708","https://openalex.org/W6620707391"],"related_works":["https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W2362101859","https://openalex.org/W2791431590","https://openalex.org/W2941610985","https://openalex.org/W4235810826","https://openalex.org/W2350688482","https://openalex.org/W2122135111","https://openalex.org/W2053575972","https://openalex.org/W2080782477"],"abstract_inverted_index":{"Accurate":[0],"identification":[1,71],"of":[2,12,35,44,160,167],"road":[3],"intersections":[4],"is":[5,53,81],"the":[6,42,133,157,165],"pivotal":[7],"task":[8],"for":[9,55,138,147],"automatic":[10],"construction":[11],"high-definition":[13],"maps,":[14,90],"particularly":[15],"in":[16],"unstructured":[17],"scenes.":[18],"Existing":[19],"methods":[20],"predominantly":[21],"rely":[22],"on":[23],"single-modal":[24],"data":[25,47,86],"and":[26,49,93,118,164],"thus":[27],"show":[28],"an":[29,73],"obvious":[30],"unimodal":[31],"limitation,":[32],"i.e.,":[33,88],"lack":[34],"contextual":[36],"information.":[37],"Moreover,":[38],"these":[39],"approaches":[40],"overlook":[41],"benefits":[43],"leveraging":[45],"multi-modal":[46,65,135],"fusion":[48,80],"representation":[50],"learning":[51,66],"that":[52],"crucial":[54],"generalizability.":[56],"To":[57,127],"this":[58],"end,":[59],"we":[60,102,131],"propose":[61],"a":[62,97],"novel":[63],"orientation-aware":[64],"paradigm,":[67],"which":[68],"formulates":[69],"intersection":[70],"as":[72],"oriented":[74],"object":[75],"detection":[76],"task.":[77],"Specifically,":[78],"heterogeneous":[79],"introduced":[82],"to":[83,107,115],"harmonize":[84],"disparate":[85],"modalities,":[87],"vector":[89],"point":[91],"clouds,":[92],"vehicle":[94],"trajectories,":[95],"into":[96],"unified":[98],"feature":[99],"space.":[100],"Concurrently,":[101],"present":[103],"trigonometry-induced":[104],"adaptive":[105],"regression":[106],"elevate":[108],"orientation":[109],"estimation,":[110],"while":[111],"mitigating":[112],"issues":[113],"related":[114],"scale":[116],"imbalance":[117],"boundary":[119],"confusion":[120],"through":[121],"dual-objective":[122],"matching":[123],"with":[124,143],"spatial":[125],"adaptation.":[126],"evaluate":[128],"our":[129,161],"methodology,":[130],"assemble":[132],"first-of-its-kind":[134],"benchmark":[136],"tailored":[137],"complex":[139],"low-speed":[140],"environments,":[141],"complete":[142],"fine-grained":[144],"semantic":[145],"annotations":[146],"intersections.":[148],"Comprehensive":[149],"empirical":[150],"analyses,":[151],"including":[152],"ablation":[153],"studies,":[154],"affirm":[155],"both":[156],"superior":[158],"performance":[159],"proposed":[162],"framework":[163],"efficacy":[166],"its":[168],"constituent":[169],"modules.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
