{"id":"https://openalex.org/W4391692135","doi":"https://doi.org/10.1007/s11063-024-11447-w","title":"Improving 3D Object Detection with Context-Aware and Dimensional Interaction Attention","display_name":"Improving 3D Object Detection with Context-Aware and Dimensional Interaction Attention","publication_year":2024,"publication_date":"2024-02-09","ids":{"openalex":"https://openalex.org/W4391692135","doi":"https://doi.org/10.1007/s11063-024-11447-w"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-024-11447-w","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11063-024-11447-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11447-w.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11447-w.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101850837","display_name":"Jing Zhou","orcid":"https://orcid.org/0000-0002-4294-3985"},"institutions":[{"id":"https://openalex.org/I31590910","display_name":"Jianghan University","ror":"https://ror.org/041c9x778","country_code":"CN","type":"education","lineage":["https://openalex.org/I31590910"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Zhou","raw_affiliation_strings":["School of Artificial Intelligence, Jianghan University, Wuhan, 430056, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jianghan University, Wuhan, 430056, China","institution_ids":["https://openalex.org/I31590910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101295647","display_name":"Zixin Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I31590910","display_name":"Jianghan University","ror":"https://ror.org/041c9x778","country_code":"CN","type":"education","lineage":["https://openalex.org/I31590910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixin Gong","raw_affiliation_strings":["School of Artificial Intelligence, Jianghan University, Wuhan, 430056, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jianghan University, Wuhan, 430056, China","institution_ids":["https://openalex.org/I31590910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029363494","display_name":"Junchi Zhang","orcid":"https://orcid.org/0000-0001-7701-568X"},"institutions":[{"id":"https://openalex.org/I31590910","display_name":"Jianghan University","ror":"https://ror.org/041c9x778","country_code":"CN","type":"education","lineage":["https://openalex.org/I31590910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junchi Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Jianghan University, Wuhan, 430056, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jianghan University, Wuhan, 430056, China","institution_ids":["https://openalex.org/I31590910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101850837"],"corresponding_institution_ids":["https://openalex.org/I31590910"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.2446,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45165228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"56","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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/computer-science","display_name":"Computer science","score":0.8426034450531006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7390867471694946},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.636540412902832},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6046198606491089},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5710512399673462},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5517300963401794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5405328273773193},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5250977277755737},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.5193737149238586},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5154114961624146},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5083796381950378},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5042299032211304},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5010521411895752},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44706493616104126},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4290100038051605},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42716288566589355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8426034450531006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7390867471694946},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.636540412902832},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6046198606491089},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5710512399673462},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5517300963401794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5405328273773193},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5250977277755737},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.5193737149238586},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5154114961624146},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5083796381950378},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5042299032211304},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5010521411895752},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44706493616104126},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4290100038051605},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42716288566589355},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-024-11447-w","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11063-024-11447-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11447-w.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-024-11447-w","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11063-024-11447-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11447-w.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3327431884","display_name":null,"funder_award_id":"2021CFB564","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G964323789","display_name":null,"funder_award_id":"62106086","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null},{"id":"https://openalex.org/F4320326959","display_name":"Jianghan University","ror":"https://ror.org/041c9x778"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4391692135.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2555618208","https://openalex.org/W2752782242","https://openalex.org/W2798965597","https://openalex.org/W2884585870","https://openalex.org/W2897529137","https://openalex.org/W2949708697","https://openalex.org/W2963351448","https://openalex.org/W2968296999","https://openalex.org/W2981949127","https://openalex.org/W3034314779","https://openalex.org/W3034552520","https://openalex.org/W3034681945","https://openalex.org/W3035172746","https://openalex.org/W3035346742","https://openalex.org/W3159695738","https://openalex.org/W3166089996","https://openalex.org/W3166470370","https://openalex.org/W3167732492","https://openalex.org/W3171377125","https://openalex.org/W3177276051","https://openalex.org/W3205005447","https://openalex.org/W3207921941","https://openalex.org/W3209035582","https://openalex.org/W4200629389","https://openalex.org/W4214777292","https://openalex.org/W4283014947","https://openalex.org/W4312410080","https://openalex.org/W4312546175","https://openalex.org/W4312934050","https://openalex.org/W4322627674","https://openalex.org/W4386065523","https://openalex.org/W6600234944"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W2154063878","https://openalex.org/W4231274751","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1538046993","https://openalex.org/W2571255492","https://openalex.org/W2963610131"],"abstract_inverted_index":{"Abstract":[0],"Recently,":[1],"3D":[2,50,88],"object":[3,51],"detection":[4,43,52,78,213],"technology":[5],"based":[6],"on":[7,204],"point":[8],"clouds":[9],"has":[10],"developed":[11],"rapidly.":[12],"However,":[13],"too":[14,33],"few":[15],"points":[16],"of":[17,71,126,132,173,190,197,215],"distant":[18],"and":[19,27,55,95,104,129,139,187,207,227],"occluded":[20],"objects":[21,30,198,223],"are":[22],"scanned":[23],"by":[24],"the":[25,42,68,72,76,82,87,123,127,140,150,159,178,182,185,205,211],"sensor,":[26],"thus":[28,74,154],"these":[29],"suffer":[31],"from":[32],"insufficient":[34],"features":[35,113,176,192],"to":[36,61,91,110,121,145,149,170,193,218],"be":[37],"detected.":[38],"This":[39],"case":[40],"damages":[41],"accuracy.":[44],"Therefore,":[45],"we":[46,85,162],"constitute":[47],"a":[48,98,105,164],"novel":[49],"with":[53],"Context-aware":[54],"dimensional":[56],"Interaction":[57,166],"Attention":[58,101,167],"Network":[59],"(CIANet)":[60],"explore":[62],"vital":[63],"geometric":[64],"cues":[65],"for":[66,114,199,222],"enriching":[67],"feature":[69],"representation":[70],"object,":[73],"boosting":[75],"overall":[77],"performance.":[79],"Specifically,":[80],"in":[81],"first":[83],"stage,":[84,161],"employ":[86],"sparse":[89],"convolution":[90],"extract":[92],"voxel":[93,112],"features,":[94,138,153],"then":[96],"construct":[97,163],"Channel-Spatial":[99],"Hybrid":[100],"(CSHA)":[102],"module":[103,109,119,142,169],"Contextual":[106],"Self-Attention":[107],"(CSA)":[108],"enhance":[111,122],"generating":[115,155],"proposals.":[116,157,179],"The":[117],"CSHA":[118],"aims":[120],"key":[124],"information":[125,148],"channel":[128,186],"spatial":[130,188],"domains":[131],"2D":[133],"Bird\u2019s":[134],"Eye":[135],"View":[136],"(BEV)":[137],"CSA":[141],"is":[143],"applied":[144],"supplement":[146],"contextual":[147],"enhanced":[151],"BEV":[152],"accurate":[156,195],"In":[158],"second":[160],"Dimensional":[165],"(DIA)":[168],"refine":[171],"Region":[172],"Interest":[174],"(RoI)":[175],"within":[177],"It":[180],"enhances":[181],"interactions":[183],"among":[184],"dimensions":[189],"RoI":[191],"learn":[194],"boundaries":[196],"proposal":[200],"refinement.":[201],"Extensive":[202],"experiments":[203],"KITTI":[206],"Waymo":[208],"benchmarks":[209],"show":[210],"superior":[212],"performance":[214],"CIANet":[216],"compared":[217],"recent":[219],"methods,":[220],"especially":[221],"such":[224],"as":[225],"pedestrians":[226],"cyclists.":[228]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
