{"id":"https://openalex.org/W7151520677","doi":"https://doi.org/10.48550/arxiv.2604.04513","title":"MPTF-Net: Multi-view Pyramid Transformer Fusion Network for LiDAR-based Place Recognition","display_name":"MPTF-Net: Multi-view Pyramid Transformer Fusion Network for LiDAR-based Place Recognition","publication_year":2026,"publication_date":"2026-04-06","ids":{"openalex":"https://openalex.org/W7151520677","doi":"https://doi.org/10.48550/arxiv.2604.04513"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.04513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.04513","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133096438","display_name":"Shuyuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Shuyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133093988","display_name":"Zihang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zihang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133066536","display_name":"Xieyuanli Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xieyuanli","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133123037","display_name":"Wenkai Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Wenkai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133085171","display_name":"Xiaoteng Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Xiaoteng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039079852","display_name":"Peizhou Ni","orcid":"https://orcid.org/0000-0002-1684-9936"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ni, Peizhou","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133096434","display_name":"Junhao Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Junhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133102123","display_name":"Dong Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Dong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5133096438"],"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.8726000189781189,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.8726000189781189,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0544000007212162,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.025800000876188278,"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/inference","display_name":"Inference","score":0.5703999996185303},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4855000078678131},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4544000029563904},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4269999861717224},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3846000134944916},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3765000104904175},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.3386000096797943},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.3199000060558319},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.3124000132083893}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7146000266075134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6452000141143799},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5703999996185303},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5146999955177307},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4544000029563904},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3765000104904175},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3199000060558319},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.3124000132083893},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2635999917984009},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.04513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.04513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"LiDAR-based":[0],"place":[1],"recognition":[2],"(LPR)":[3],"is":[4,31,87],"essential":[5],"for":[6,28,178],"global":[7,20],"localization":[8],"and":[9,42,99,133,145],"loop-closure":[10],"detection":[11],"in":[12,65],"large-scale":[13],"SLAM":[14],"systems.":[15,182],"Existing":[16],"methods":[17],"typically":[18],"construct":[19],"descriptors":[21],"from":[22],"Range":[23,129],"Images":[24],"or":[25,67],"BEV":[26,30,47,91],"representations":[27,48],"matching.":[29],"widely":[32],"adopted":[33],"due":[34],"to":[35,56,62],"its":[36],"explicit":[37],"2D":[38],"spatial":[39,137],"layout":[40],"encoding":[41,92],"efficient":[43],"retrieval.":[44],"However,":[45],"conventional":[46],"rely":[49],"on":[50,141,160],"simple":[51],"statistical":[52],"aggregation,":[53],"which":[54],"fails":[55],"capture":[57],"fine-grained":[58],"geometric":[59,97],"structures,":[60],"leading":[61],"performance":[63],"degradation":[64],"complex":[66],"repetitive":[68],"environments.":[69],"To":[70,111],"address":[71],"this,":[72],"we":[73,116],"propose":[74],"MPTF-Net,":[75],"a":[76,88,107,118,156],"novel":[77],"multi-view":[78],"multi-scale":[79],"pyramid":[80,120],"Transformer":[81,121],"fusion":[82],"network.":[83],"Our":[84],"core":[85],"contribution":[86],"multi-channel":[89],"NDT-based":[90],"that":[93,123,149],"explicitly":[94],"models":[95],"local":[96],"complexity":[98],"intensity":[100],"distributions":[101],"via":[102],"Normal":[103],"Distribution":[104],"Transform,":[105],"providing":[106],"noise-resilient":[108],"structural":[109],"prior.":[110],"effectively":[112],"integrate":[113],"these":[114],"features,":[115],"develop":[117],"customized":[119],"module":[122],"captures":[124],"cross-view":[125],"interactive":[126],"correlations":[127],"between":[128],"Image":[130],"Views":[131],"(RIV)":[132],"NDT-BEV":[134],"at":[135],"multiple":[136],"scales.":[138],"Extensive":[139],"experiments":[140],"the":[142,161],"nuScenes,":[143],"KITTI":[144],"NCLT":[146],"datasets":[147],"demonstrate":[148],"MPTF-Net":[150],"achieves":[151],"state-of-the-art":[152],"performance,":[153],"specifically":[154],"attaining":[155],"Recall@1":[157],"of":[158,170],"96.31\\%":[159],"nuScenes":[162],"Boston":[163],"split":[164],"while":[165],"maintaining":[166],"an":[167],"inference":[168],"latency":[169],"only":[171],"10.02":[172],"ms,":[173],"making":[174],"it":[175],"highly":[176],"suitable":[177],"real-time":[179],"autonomous":[180],"unmanned":[181]},"counts_by_year":[],"updated_date":"2026-04-08T06:07:18.267832","created_date":"2026-04-08T00:00:00"}
