{"id":"https://openalex.org/W4414360455","doi":"https://doi.org/10.24963/ijcai.2025/974","title":"Understanding Matters: Semantic-Structural Determined Visual Relocalization for Large Scenes","display_name":"Understanding Matters: Semantic-Structural Determined Visual Relocalization for Large Scenes","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360455","doi":"https://doi.org/10.24963/ijcai.2025/974"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/974","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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":null,"display_name":"Jingyi Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingyi Nie","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101198416","display_name":"Liangliang Cai","orcid":"https://orcid.org/0000-0001-5381-9368"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangliang Cai","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024575685","display_name":"Qichuan Geng","orcid":"https://orcid.org/0000-0002-0046-5794"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qichuan Geng","raw_affiliation_strings":["The Information Engineering College, Capital Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Information Engineering College, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112170501","display_name":"Zhong Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Zhou","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, China","Zhongguancun Laboratory, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Zhongguancun Laboratory, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3193777,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8759","last_page":"8767"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.5335999727249146,"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"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.5335999727249146,"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"}},{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.4925000071525574,"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/partition","display_name":"Partition (number theory)","score":0.5756999850273132},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5357000231742859},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5300999879837036},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.47780001163482666},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4722999930381775},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45509999990463257},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.43070000410079956},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.3950999975204468},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.3686999976634979}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.692799985408783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.692300021648407},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5756999850273132},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5357000231742859},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5300999879837036},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.47780001163482666},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45509999990463257},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.43070000410079956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41589999198913574},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3950999975204468},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.3686999976634979},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3465000092983246},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3084999918937683},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.28999999165534973},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/974","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"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":{"Scene":[0],"Coordinate":[1],"Regression":[2],"(SCR)":[3],"estimates":[4],"3D":[5,68],"scene":[6,49,115],"coordinates":[7],"from":[8],"2D":[9],"images,":[10],"and":[11,45,57,96,105,125,151,159,175],"has":[12],"become":[13],"an":[14],"important":[15],"approach":[16],"in":[17,26,34,42],"visual":[18],"relocalization.":[19],"Existing":[20],"methods":[21],"exhibit":[22],"high":[23],"localization":[24],"accuracy":[25],"small":[27,117],"scenes,":[28,36,203],"but":[29],"still":[30],"face":[31],"substantial":[32],"challenges":[33],"large-scale":[35,202],"which":[37,91],"usually":[38],"have":[39],"significant":[40,195],"variations":[41],"depth,":[43],"scale,":[44],"occlusion.":[46],"Although":[47],"structure-guided":[48],"partitioning":[50],"is":[51,133,218],"commonly":[52],"adopted,":[53],"the":[54,64,67,78,83,103,114,144,185,191,205,212],"over-partitioned":[55],"elements":[56],"large":[58,109],"feature":[59,168],"variances":[60],"within":[61,128],"subscenes":[62,118],"impede":[63],"estimation":[65],"of":[66],"coordinates,":[69],"introducing":[70],"misleading":[71],"information":[72,107],"for":[73,89,156],"subsequent":[74,180],"processing.":[75],"To":[76,165],"address":[77],"above-mentioned":[79],"issues,":[80],"we":[81,112,170],"propose":[82],"Semantic-Structural":[84],"Determined":[85],"Visual":[86],"Relocalization":[87],"method":[88,193,215],"SCR,":[90],"leverages":[92],"semantic-structural":[93],"partition":[94,113,145],"learning":[95,138],"partition-determined":[97],"pose":[98],"refinement":[99],"to":[100,139,211],"better":[101],"understand":[102],"semantic":[104,123],"structural":[106,126],"on":[108,184,201],"scenes.":[110],"Firstly,":[111],"into":[116,149],"with":[119,136,153,197],"label":[120],"assignments,":[121],"ensuring":[122],"consistency":[124],"continuity":[127],"each":[129],"subscene.":[130],"A":[131],"classifier":[132],"then":[134],"trained":[135],"sampling-based":[137],"predict":[140],"these":[141],"labels.":[142],"Secondly,":[143],"predictions":[146],"are":[147],"encoded":[148],"embeddings":[150],"integrated":[152],"local":[154],"features":[155],"intra-class":[157],"compactness":[158],"inter-class":[160],"separation,":[161],"producing":[162],"partition-aware":[163],"features.":[164],"further":[166],"decrease":[167],"variances,":[169],"employ":[171],"a":[172],"discriminability":[173],"metric":[174],"suppress":[176],"ambiguous":[177],"points,":[178],"improving":[179],"computations.":[181],"Experimental":[182],"results":[183],"Cambridge":[186],"Landmarks":[187],"dataset":[188],"demonstrate":[189],"that":[190],"proposed":[192],"achieves":[194],"improvements":[196],"fewer":[198],"training":[199],"costs":[200],"reducing":[204],"median":[206],"error":[207],"by":[208],"38%":[209],"compared":[210],"state-of-the-art":[213],"SCR":[214],"DSAC*.":[216],"Code":[217],"available:":[219],"https://gitee.com/VR_NAVE/ss-dvr.":[220]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
