{"id":"https://openalex.org/W7155069009","doi":"https://doi.org/10.48550/arxiv.2604.16696","title":"LOD-Net: Locality-Aware 3D Object Detection Using Multi-Scale Transformer Network","display_name":"LOD-Net: Locality-Aware 3D Object Detection Using Multi-Scale Transformer Network","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7155069009","doi":"https://doi.org/10.48550/arxiv.2604.16696"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.16696","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16696","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.16696","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075409562","display_name":"Mustaqeem Khan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Mustaqeem","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020726719","display_name":"Aidana Nurakhmetova","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nurakhmetova, Aidana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036560577","display_name":"Wail Gueaieb","orcid":"https://orcid.org/0000-0001-6490-4648"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gueaieb, Wail","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134185037","display_name":"Abdulmotaleb El Saddik","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saddik, Abdulmotaleb El","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":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.6552000045776367,"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":0.6552000045776367,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.22010000050067902,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.03550000116229057,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.7742999792098999},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6805999875068665},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5992000102996826},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5412999987602234},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4722999930381775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41519999504089355},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.38850000500679016},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3587999939918518},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.35440000891685486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7746000289916992},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.7742999792098999},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6805999875068665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6455000042915344},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5992000102996826},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5412999987602234},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5203999876976013},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3587999939918518},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.35440000891685486},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3529999852180481},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.31779998540878296},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29989999532699585},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2809000015258789},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C141297171","wikidata":"https://www.wikidata.org/wiki/Q1143237","display_name":"Octree","level":2,"score":0.258899986743927}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.16696","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16696","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.16696","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16696","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"3D":[0,140],"object":[1],"detection":[2,85],"in":[3,21,93,97,138],"point":[4],"cloud":[5],"data":[6],"remains":[7],"a":[8,29,88],"challenging":[9],"task":[10],"due":[11],"to":[12,40,63,105],"the":[13,22,37,61,74,100,106,115,119,128],"sparsity":[14],"and":[15,46,67,95],"lack":[16],"of":[17,90,117,130],"global":[18,47],"structure":[19],"inherent":[20],"input.":[23],"In":[24],"this":[25],"work,":[26],"we":[27],"propose":[28],"novel":[30],"Multi-Scale":[31],"Attention":[32],"(MSA)":[33],"mechanism":[34],"integrated":[35],"into":[36],"3DETR":[38,80],"architecture":[39],"better":[41,64],"capture":[42],"both":[43],"local":[44],"geometry":[45],"context.":[48],"Our":[49],"method":[50],"introduces":[51],"an":[52],"upsampling":[53,120],"operation":[54],"that":[55,78],"generates":[56],"high-resolution":[57],"feature":[58,133],"maps,":[59],"enabling":[60],"network":[62],"detect":[65],"smaller":[66],"semantically":[68],"related":[69],"objects.":[70],"Experiments":[71],"conducted":[72],"on":[73],"ScanNetv2":[75],"dataset":[76],"demonstrate":[77],"our":[79,112],"+":[81],"MSA":[82,104],"model":[83],"improves":[84],"performance,":[86],"achieving":[87],"gain":[89],"almost":[91],"1%":[92],"mAP@25":[94],"4.78%":[96],"mAP@50":[98],"over":[99],"baseline.":[101],"While":[102],"applying":[103],"3DETR-m":[107],"variant":[108],"shows":[109],"limited":[110],"improvement,":[111],"analysis":[113],"reveals":[114],"importance":[116],"adapting":[118],"strategy":[121],"for":[122],"lightweight":[123],"models.":[124],"These":[125],"results":[126],"highlight":[127],"effectiveness":[129],"combining":[131],"hierarchical":[132],"extraction":[134],"with":[135],"attention":[136],"mechanisms":[137],"enhancing":[139],"scene":[141],"understanding.":[142]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-22T00:00:00"}