{"id":"https://openalex.org/W4413918268","doi":"https://doi.org/10.1109/icra55743.2025.11127818","title":"Directed-CP: Directed Collaborative Perception for Connected and Autonomous Vehicles via Proactive Attention","display_name":"Directed-CP: Directed Collaborative Perception for Connected and Autonomous Vehicles via Proactive Attention","publication_year":2025,"publication_date":"2025-05-19","ids":{"openalex":"https://openalex.org/W4413918268","doi":"https://doi.org/10.1109/icra55743.2025.11127818"},"language":"en","primary_location":{"id":"doi:10.1109/icra55743.2025.11127818","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra55743.2025.11127818","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5040546889","display_name":"Yihang Tao","orcid":"https://orcid.org/0000-0002-9596-4106"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yihang Tao","raw_affiliation_strings":["City University of Hong Kong,Department of Computer Science,Kowloon,Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Computer Science,Kowloon,Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109769286","display_name":"Senkang Hu","orcid":"https://orcid.org/0009-0000-4129-8868"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Senkang Hu","raw_affiliation_strings":["City University of Hong Kong,Department of Computer Science,Kowloon,Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Computer Science,Kowloon,Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057427421","display_name":"Zhengru Fang","orcid":"https://orcid.org/0000-0003-0028-7892"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhengru Fang","raw_affiliation_strings":["City University of Hong Kong,Department of Computer Science,Kowloon,Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Computer Science,Kowloon,Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016290340","display_name":"Yuguang Fang","orcid":"https://orcid.org/0000-0002-1079-3871"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuguang Fang","raw_affiliation_strings":["City University of Hong Kong,Department of Computer Science,Kowloon,Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Computer Science,Kowloon,Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9349,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7858109,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"7004","last_page":"7010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9897000193595886,"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"}},"topics":[{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9897000193595886,"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6266210079193115},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6036231517791748},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5148307681083679},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.17987698316574097},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.17843803763389587}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6266210079193115},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6036231517791748},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5148307681083679},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.17987698316574097},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.17843803763389587}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra55743.2025.11127818","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra55743.2025.11127818","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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":15,"referenced_works":["https://openalex.org/W2968296999","https://openalex.org/W3035098634","https://openalex.org/W3090375251","https://openalex.org/W3109991383","https://openalex.org/W4205397442","https://openalex.org/W4206138072","https://openalex.org/W4312604822","https://openalex.org/W4383066393","https://openalex.org/W4383108477","https://openalex.org/W4383108597","https://openalex.org/W4383108819","https://openalex.org/W4383108834","https://openalex.org/W4401414597","https://openalex.org/W4401878785","https://openalex.org/W4410949473"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Collaborative":[0],"perception":[1,72,209,218],"(CP)":[2],"leverages":[3],"visual":[4],"data":[5,167],"from":[6],"connected":[7],"and":[8,87,113,164,186,214],"autonomous":[9],"vehicles":[10],"(CAV)":[11],"to":[12,66,102,107,117,151,178],"expand":[13,28],"an":[14,104,129,136],"ego":[15,30,105,137,158],"vehicle's":[16,31,159],"field":[17],"of":[18,168],"view":[19],"(FoV).":[20],"Despite":[21],"recent":[22],"progress,":[23],"current":[24],"CP":[25,89,94,121,184],"methods":[26,223],"do":[27],"the":[29,71,165,180,187,197,221],"360-degree":[32],"perceptual":[33],"range":[34],"almost":[35],"equally,":[36],"but":[37],"faces":[38],"two":[39],"key":[40,99],"challenges.":[41],"Firstly,":[42],"in":[43,74,95,139,211,224],"areas":[44],"with":[45,52],"uneven":[46],"traffic":[47,54],"distribution,":[48],"focusing":[49],"on":[50,157,196],"directions":[51,69,112,213],"little":[53],"offers":[55],"limited":[56,60],"benefits.":[57],"Secondly,":[58],"under":[59],"communication":[61,162],"budgets,":[62],"allocating":[63],"excessive":[64],"bandwidth":[65],"less":[67],"critical":[68],"lowers":[70],"accuracy":[73,210,219],"more":[75],"vital":[76,141],"areas.":[77],"To":[78,123],"address":[79],"these":[80],"issues,":[81],"we":[82,126,144,171],"propose":[83,128],"Directed-CP,":[84],"a":[85,146,173],"proactive":[86],"direction-aware":[88,147],"system":[90],"aiming":[91],"at":[92],"improving":[93],"specific":[96],"directions.":[97,142],"Our":[98],"idea":[100],"is":[101],"enable":[103],"vehicle":[106,138],"proactively":[108],"signal":[109],"its":[110,115],"interested":[111,212],"readjust":[114],"attention":[116,149],"enhance":[118],"local":[119,208],"directional":[120,160,183],"performance.":[122],"achieve":[124],"this,":[125],"first":[127],"RSU-aided":[130],"direction":[131],"masking":[132],"mechanism":[133],"that":[134,202],"assists":[135],"identifying":[140],"Additionally,":[143],"design":[145],"selective":[148],"module":[150],"wisely":[152],"aggregate":[153],"pertinent":[154],"features":[155],"based":[156],"priorities,":[161],"budget,":[163],"positional":[166],"CAVs.":[169],"Moreover,":[170],"introduce":[172],"direction-weighted":[174],"detection":[175,228],"loss":[176],"(DWLoss)":[177],"capture":[179],"divergence":[181],"between":[182],"outcomes":[185],"ground":[188],"truth,":[189],"facilitating":[190],"effective":[191],"model":[192],"training.":[193],"Extensive":[194],"experiments":[195],"V2X-Sim":[198],"2.0":[199],"dataset":[200],"demonstrate":[201],"our":[203],"approach":[204],"achieves":[205],"19.8%":[206],"higher":[207,216],"2.5%":[215],"overall":[217],"than":[220],"state-of-the-art":[222],"collaborative":[225],"3D":[226],"object":[227],"tasks.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
