{"id":"https://openalex.org/W7162504975","doi":"https://doi.org/10.1109/3dv69130.2026.00061","title":"3D Scene Change Modeling With Consistent Multi-View Aggregation","display_name":"3D Scene Change Modeling With Consistent Multi-View Aggregation","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7162504975","doi":"https://doi.org/10.1109/3dv69130.2026.00061"},"language":null,"primary_location":{"id":"doi:10.1109/3dv69130.2026.00061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-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/A5101058817","display_name":"Zirui Zhou","orcid":"https://orcid.org/0009-0002-5761-2828"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zirui Zhou","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132880032","display_name":"Junfeng Ni","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfeng Ni","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101904356","display_name":"Shujie Zhang","orcid":"https://orcid.org/0000-0003-4880-9856"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shujie Zhang","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393447","display_name":"Yixin Chen","orcid":"https://orcid.org/0000-0002-6605-1615"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixin Chen","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137177965","display_name":"Siyuan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyuan Huang","raw_affiliation_strings":["State Key Laboratory of General Artificial Intelligence, BIGAI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of General Artificial Intelligence, BIGAI","institution_ids":["https://openalex.org/I4210100255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85252308,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"576","last_page":"586"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.4569999873638153,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.4569999873638153,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.1160999983549118,"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":0.10000000149011612,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.28600001335144043},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.2831999957561493},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.2815000116825104},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.25760000944137573},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.2517000138759613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5407999753952026},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5084999799728394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4936000108718872},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2517000138759613},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2475000023841858},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.24690000712871552}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/3dv69130.2026.00061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.40355250239372253}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W2027461913","https://openalex.org/W2053750911","https://openalex.org/W2097838991","https://openalex.org/W2118116484","https://openalex.org/W2144552105","https://openalex.org/W2471962767","https://openalex.org/W2519683295","https://openalex.org/W2610207162","https://openalex.org/W2891590884","https://openalex.org/W3003179103","https://openalex.org/W3030364939","https://openalex.org/W3090836511","https://openalex.org/W3109585842","https://openalex.org/W3130635958","https://openalex.org/W3159481202","https://openalex.org/W3180045188","https://openalex.org/W4312549298","https://openalex.org/W4312971576","https://openalex.org/W4312979941","https://openalex.org/W4377079808","https://openalex.org/W4385318467","https://openalex.org/W4386076284","https://openalex.org/W4390848649","https://openalex.org/W4390872170","https://openalex.org/W4390872457","https://openalex.org/W4393241168","https://openalex.org/W4399344797","https://openalex.org/W4400819283","https://openalex.org/W4401018268","https://openalex.org/W4401990337","https://openalex.org/W4402702918","https://openalex.org/W4402961810","https://openalex.org/W4403841834","https://openalex.org/W4404002612","https://openalex.org/W4405003283","https://openalex.org/W4406812170","https://openalex.org/W4409346685","https://openalex.org/W4413144631","https://openalex.org/W4413146003","https://openalex.org/W4415707176","https://openalex.org/W4415796579","https://openalex.org/W4415798462","https://openalex.org/W4415800492","https://openalex.org/W7138030777","https://openalex.org/W7139091869","https://openalex.org/W7160038030","https://openalex.org/W7160046300","https://openalex.org/W7160115585","https://openalex.org/W7160299844"],"related_works":[],"abstract_inverted_index":{"Change":[0],"detection":[1,16,47],"plays":[2],"a":[3,42,54,67,96,115],"vital":[4],"role":[5],"in":[6,22],"scene":[7,45,98],"monitoring,":[8],"exploration,":[9],"and":[10,26,32,59,78,90,141],"continual":[11,97],"reconstruction.":[12],"Existing":[13],"3D":[14,44,124],"change":[15,46,125],"methods":[17],"often":[18],"exhibit":[19],"spatial":[20],"inconsistency":[21],"the":[23,81,108],"detected":[24],"changes":[25,52],"fail":[27],"to":[28,86,127],"explicitly":[29],"separate":[30,88],"pre-":[31,89],"post-change":[33,61,91],"states.":[34,92],"To":[35],"address":[36],"these":[37],"limitations,":[38],"we":[39],"propose":[40],"SCAR-3D,":[41],"novel":[43],"framework":[48],"that":[49,101,119,134],"identifies":[50],"object-level":[51],"from":[53],"dense-view":[55],"pre-change":[56],"image":[57],"sequence":[58],"sparse-view":[60],"images.":[62],"Our":[63],"approach":[64],"consists":[65],"of":[66,84,123],"signed-distance-based":[68],"2D":[69],"differencing":[70],"module":[71],"followed":[72],"by":[73],"multiview":[74],"aggregation":[75],"with":[76],"voting":[77],"pruning,":[79],"leveraging":[80],"consistent":[82],"nature":[83],"3DGS":[85],"robustly":[87],"We":[93,111],"further":[94],"develop":[95],"reconstruction":[99],"strategy":[100],"selectively":[102],"updates":[103],"dynamic":[104],"regions":[105],"while":[106],"preserving":[107],"unchanged":[109],"areas.":[110],"also":[112],"contribute":[113],"CCS3D,":[114],"challenging":[116],"synthetic":[117],"dataset":[118],"allows":[120],"flexible":[121],"combinations":[122],"types":[126],"support":[128],"controlled":[129],"evaluations.":[130],"Extensive":[131],"experiments":[132],"demonstrate":[133],"our":[135],"method":[136],"achieves":[137],"both":[138],"high":[139],"accuracy":[140],"efficiency,":[142],"outperforming":[143],"existing":[144],"methods.":[145]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-28T00:00:00"}
