{"id":"https://openalex.org/W7128776249","doi":"https://doi.org/10.1109/lra.2026.3664657","title":"GPR-Net: Geometric-Positional Collaborative Point Cloud Registration Network for Repetitive Geometric Structures","display_name":"GPR-Net: Geometric-Positional Collaborative Point Cloud Registration Network for Repetitive Geometric Structures","publication_year":2026,"publication_date":"2026-02-13","ids":{"openalex":"https://openalex.org/W7128776249","doi":"https://doi.org/10.1109/lra.2026.3664657"},"language":null,"primary_location":{"id":"doi:10.1109/lra.2026.3664657","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2026.3664657","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-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/A5105015418","display_name":"Xiaohui Lu","orcid":"https://orcid.org/0009-0006-8707-2155"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Lu","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0006-8707-2155","affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125933222","display_name":"Jianhu Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhu Nie","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-5826-0874","affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22421796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"4","first_page":"3979","last_page":"3985"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.6144999861717224,"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":0.6144999861717224,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.25780001282691956,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.05700000002980232,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.703000009059906},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6481999754905701},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5386999845504761},{"id":"https://openalex.org/keywords/correspondence-problem","display_name":"Correspondence problem","score":0.46389999985694885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.447299987077713},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.42289999127388},{"id":"https://openalex.org/keywords/geometric-shape","display_name":"Geometric shape","score":0.4075999855995178},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.39410001039505005},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.38029998540878296},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.36649999022483826}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.703000009059906},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6639000177383423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6575000286102295},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6481999754905701},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5386999845504761},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48590001463890076},{"id":"https://openalex.org/C3004257","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Correspondence problem","level":2,"score":0.46389999985694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.447299987077713},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.38029998540878296},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.35749998688697815},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.35199999809265137},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.3393000066280365},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.30399999022483826},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C181095308","wikidata":"https://www.wikidata.org/wiki/Q1541599","display_name":"Geometric primitive","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C136520226","wikidata":"https://www.wikidata.org/wiki/Q302814","display_name":"Geometric data analysis","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C49777392","wikidata":"https://www.wikidata.org/wiki/Q5535495","display_name":"Geometric networks","level":3,"score":0.2660999894142151},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.25519999861717224},{"id":"https://openalex.org/C53471067","wikidata":"https://www.wikidata.org/wiki/Q7574076","display_name":"Spatial network","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2026.3664657","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2026.3664657","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.614295482635498,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2733558714","display_name":null,"funder_award_id":"61802204","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1972485825","https://openalex.org/W2083624955","https://openalex.org/W2118987544","https://openalex.org/W2160821342","https://openalex.org/W2270425654","https://openalex.org/W2344109021","https://openalex.org/W2560609797","https://openalex.org/W2566265240","https://openalex.org/W2605618441","https://openalex.org/W2792346134","https://openalex.org/W2810431401","https://openalex.org/W2883357174","https://openalex.org/W2962828767","https://openalex.org/W2962941647","https://openalex.org/W2963264709","https://openalex.org/W2963666542","https://openalex.org/W2963847924","https://openalex.org/W2979750740","https://openalex.org/W2981995220","https://openalex.org/W2986382673","https://openalex.org/W3013243617","https://openalex.org/W3034295752","https://openalex.org/W4287281274","https://openalex.org/W4312773339","https://openalex.org/W4328007191","https://openalex.org/W4376271879","https://openalex.org/W4386590175","https://openalex.org/W4387765888","https://openalex.org/W4388494032","https://openalex.org/W4389219530","https://openalex.org/W4390956176","https://openalex.org/W4393183790","https://openalex.org/W4394564083","https://openalex.org/W4398202290","https://openalex.org/W4399563284","https://openalex.org/W4399564035","https://openalex.org/W4400276168","https://openalex.org/W4401460431","https://openalex.org/W4406135481"],"related_works":[],"abstract_inverted_index":{"Point":[0],"cloud":[1],"registration":[2,13,154,183],"is":[3],"a":[4,53,68,83,93,119],"critical":[5],"task":[6],"for":[7,128],"building":[8],"complete":[9],"3D":[10],"models.":[11],"Existing":[12],"methods":[14],"primarily":[15],"focus":[16],"on":[17,163],"correspondence":[18,55,130],"relationships":[19],"between":[20],"points,":[21],"often":[22],"using":[23,71],"local":[24,79],"geometric":[25,41,59,103,124,189],"features":[26,42,62,127],"to":[27,44,76,86,97,140,157],"determine":[28],"matches.":[29],"However,":[30],"this":[31,112],"approach":[32],"generates":[33],"numerous":[34],"false":[35],"matches":[36],"in":[37,137,147,182],"scenes":[38],"with":[39],"repetitive":[40,148,188],"due":[43],"similar":[45,176],"structures.":[46],"To":[47],"address":[48],"this,":[49],"we":[50,117,133,151],"propose":[51],"GPR-Net,":[52],"collaborative":[54,94],"discrimination":[56,95],"network":[57],"combining":[58],"and":[60,105,125,144,165,185],"positional":[61,126],"of":[63,111],"points.":[64],"This":[65],"method":[66,171],"constructs":[67],"geometry":[69],"branch":[70,85],"Dynamic":[72],"Graph":[73],"CNN":[74],"(DGCNN)":[75],"extract":[77],"multi-scale":[78],"features,":[80],"while":[81],"introducing":[82],"position":[84],"encode":[87],"global":[88],"spatial":[89,106],"distributions.":[90],"It":[91],"employs":[92],"mechanism":[96],"select":[98],"point":[99],"pairs":[100],"exhibiting":[101],"both":[102,138],"similarity":[104],"consistency.":[107],"The":[108],"main":[109],"contributions":[110],"work":[113],"are":[114],"threefold:":[115],"(1)":[116],"design":[118],"dual-branch":[120],"framework":[121],"that":[122],"integrates":[123],"robust":[129],"discrimination;":[131],"(2)":[132],"introduce":[134],"contrastive":[135],"constraints":[136],"branches":[139],"enhance":[141],"feature":[142,180,190],"distinctiveness":[143],"reduce":[145],"mismatches":[146],"structures;":[149],"(3)":[150],"demonstrate":[152],"superior":[153],"results":[155],"compared":[156],"state-of-the-art":[158],"descriptors":[159,181],"through":[160],"extensive":[161],"experiments":[162],"ModelNet40":[164],"noisy":[166],"datasets.":[167],"Experiments":[168],"show":[169],"our":[170],"effectively":[172],"counteracts":[173],"interference":[174],"from":[175],"structures,":[177],"outperforming":[178],"mainstream":[179],"accuracy":[184],"robustness":[186],"within":[187],"scenes.":[191]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-02-14T00:00:00"}