{"id":"https://openalex.org/W7136120533","doi":"https://doi.org/10.1109/itsc60802.2025.11423783","title":"LoECSNet: A Local Expansion and Cross-Row Sampling Self-Attention Network for 3D Object Detection","display_name":"LoECSNet: A Local Expansion and Cross-Row Sampling Self-Attention Network for 3D Object Detection","publication_year":2025,"publication_date":"2025-11-18","ids":{"openalex":"https://openalex.org/W7136120533","doi":"https://doi.org/10.1109/itsc60802.2025.11423783"},"language":null,"primary_location":{"id":"doi:10.1109/itsc60802.2025.11423783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423783","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5109737208","display_name":"Zenan Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ZeNan Bai","raw_affiliation_strings":["The School of Software Engineering, Xi'an Jiaotong University,Xi'an,China,710049"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The School of Software Engineering, Xi'an Jiaotong University,Xi'an,China,710049","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110814145","display_name":"Yonghong Song","orcid":"https://orcid.org/0000-0001-5978-3781"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"YongHong Song","raw_affiliation_strings":["The School of Software Engineering, Xi'an Jiaotong University,Xi'an,China,710049"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The School of Software Engineering, Xi'an Jiaotong University,Xi'an,China,710049","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129567247","display_name":"ZeYu Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ZeYu Meng","raw_affiliation_strings":["The Institution of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Institution of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028863659","display_name":"Xiaomeng Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"XiaoMeng Wu","raw_affiliation_strings":["The School of Software Engineering, Xi'an Jiaotong University,Xi'an,China,710049"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The School of Software Engineering, Xi'an Jiaotong University,Xi'an,China,710049","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87445476"],"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":"4121","last_page":"4128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8104000091552734,"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":0.8104000091552734,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.02889999933540821,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.01590000092983246,"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/object-detection","display_name":"Object detection","score":0.4918999969959259},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4562000036239624},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43290001153945923},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3824999928474426},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.36970001459121704},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.28290000557899475}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6122999787330627},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5824000239372253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5547999739646912},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4918999969959259},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4562000036239624},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43290001153945923},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.36970001459121704},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.2648000121116638},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2583000063896179},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2515000104904175},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc60802.2025.11423783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423783","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","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":25,"referenced_works":["https://openalex.org/W1513100184","https://openalex.org/W2897529137","https://openalex.org/W2963727135","https://openalex.org/W2968296999","https://openalex.org/W3035346742","https://openalex.org/W3035574168","https://openalex.org/W3109675406","https://openalex.org/W3166470370","https://openalex.org/W3167095230","https://openalex.org/W3176231905","https://openalex.org/W3177052299","https://openalex.org/W4225865900","https://openalex.org/W4226098442","https://openalex.org/W4289752563","https://openalex.org/W4308080803","https://openalex.org/W4312707458","https://openalex.org/W4367182782","https://openalex.org/W4367281358","https://openalex.org/W4386076253","https://openalex.org/W4391768718","https://openalex.org/W4402716222","https://openalex.org/W4402896333","https://openalex.org/W4404520687","https://openalex.org/W4408046274","https://openalex.org/W4408696501"],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"driving":[1,27],"systems":[2],"integrate":[3],"3D":[4,18,35,46,95],"object":[5,19,47,96],"detection":[6,20,48,77],"to":[7],"enhance":[8],"the":[9,112,119,135,152,165],"efficiency":[10],"and":[11,69,72,89,148,181],"safety":[12],"of":[13,32],"intelligent":[14],"transportation":[15],"systems.":[16,28],"LiDAR-based":[17],"plays":[21],"a":[22,86,101],"crucial":[23],"role":[24],"in":[25,34,66,75,146,177],"autonomous":[26],"The":[29],"sparse":[30,58],"distribution":[31],"points":[33],"scenes":[36],"typically":[37,50],"causes":[38],"long-range":[39,142],"feature":[40],"dependency":[41],"loss,":[42],"which":[43],"existing":[44],"high-performance":[45],"methods":[49,62],"address":[51,80],"by":[52],"redesigning":[53],"backbone":[54],"networks":[55],"or":[56],"using":[57],"detectors.":[59],"However,":[60],"previous":[61,171],"exhibit":[63],"significant":[64],"limitations":[65],"utilizing":[67],"context":[68],"balancing":[70],"time":[71],"space,":[73,147],"resulting":[74],"unsatisfactory":[76],"outcomes.":[78],"To":[79],"these":[81,123],"issues,":[82],"we":[83],"propose":[84],"LoECSNet,":[85],"Local":[87],"Expansion":[88],"Cross-Line":[90],"Sampling":[91],"Self-Attention":[92,137],"Network":[93],"for":[94,106,158],"detection.":[97,159],"We":[98,160],"first":[99],"designed":[100],"local":[102],"partitioning":[103],"expansion(LE)":[104],"block":[105,117,140],"generating":[107],"expansion":[108,124],"windows.":[109],"After":[110],"that,":[111],"spatialcontent":[113],"adaptive":[114,127,155],"interaction":[115,128,156],"(SAI)":[116],"transforms":[118],"BEV":[120],"features":[121,129,145,157],"within":[122],"windows":[125],"into":[126],"that":[130],"incorporate":[131],"contextual":[132],"information.":[133],"Finally,":[134],"Cross-row":[136],"downsampling":[138],"(CSA)":[139],"captures":[141],"dependencies":[143],"between":[144],"merges":[149],"them":[150],"with":[151],"previously":[153],"obtained":[154],"conducted":[161],"extensive":[162],"experiments":[163],"on":[164],"nuScenes":[166],"dataset,":[167],"where":[168],"LoECSNet":[169],"outperformed":[170],"state-of-the-art":[172],"methods,":[173],"demonstrating":[174],"superior":[175],"performance":[176],"detecting":[178],"large,":[179],"long-range,":[180],"contextually":[182],"relevant":[183],"objects.":[184]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-17T00:00:00"}