{"id":"https://openalex.org/W7163580628","doi":"https://doi.org/10.48550/arxiv.2606.05011","title":"CIPER: A Unified Framework for Cross-view Image-retrieval and Pose-estimation","display_name":"CIPER: A Unified Framework for Cross-view Image-retrieval and Pose-estimation","publication_year":2026,"publication_date":"2026-06-03","ids":{"openalex":"https://openalex.org/W7163580628","doi":"https://doi.org/10.48550/arxiv.2606.05011"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.05011","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05011","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.05011","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073240279","display_name":"Yurim Jeon","orcid":"https://orcid.org/0000-0002-3033-1690"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeon, Yurim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137901942","display_name":"Dongseong Seo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seo, Dongseong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137912987","display_name":"Seung-Woo Seo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seo, Seung-Woo","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.8361999988555908,"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":0.8361999988555908,"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":0.08299999684095383,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.02710000053048134,"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/encoder","display_name":"Encoder","score":0.5604000091552734},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4837000072002411},{"id":"https://openalex.org/keywords/feature-matching","display_name":"Feature matching","score":0.4788999855518341},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4472000002861023},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4458000063896179},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4129999876022339},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.40290001034736633},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.3822999894618988},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.38119998574256897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7207000255584717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5616000294685364},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5604000091552734},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4837000072002411},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.4788999855518341},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4472000002861023},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4458000063896179},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4334999918937683},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3822999894618988},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38029998540878296},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3767000138759613},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37619999051094055},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3555000126361847},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.303600013256073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.301800012588501},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.2587999999523163},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.05011","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05011","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.05011","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05011","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.715863049030304,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Cross-view":[0],"geo-localization":[1,71],"estimates":[2],"the":[3,39,126],"geographic":[4],"location":[5],"of":[6,41],"a":[7,53,73,93,108,137,162],"ground":[8,131,144],"image":[9,16],"by":[10],"matching":[11],"it":[12],"against":[13],"an":[14],"aerial":[15,133],"database.":[17],"Existing":[18],"methods":[19,34,47],"tackle":[20],"this":[21],"through":[22,101],"either":[23],"large-scale":[24],"retrieval":[25,79,118],"or":[26],"precise":[27,81],"pose":[28,45,83,140],"estimation,":[29],"but":[30],"not":[31],"both:":[32],"retrieval-based":[33],"enable":[35],"wide-area":[36],"search":[37,55],"at":[38,187],"cost":[40],"localization":[42,122],"accuracy,":[43],"while":[44],"estimation":[46],"achieve":[48],"high":[49],"precision":[50],"within":[51],"only":[52],"narrow":[54],"space.":[56],"Naively":[57],"cascading":[58],"these":[59],"pipelines":[60],"introduces":[61],"error":[62],"propagation":[63],"and":[64,80,90,132,170,180],"inconsistent":[65],"feature":[66,104],"representations.":[67],"We":[68,85],"formulate":[69],"cross-view":[70],"as":[72,146],"unified":[74,163],"problem":[75],"requiring":[76],"simultaneous":[77],"city-scale":[78],"3-DoF":[82,159],"estimation.":[84],"propose":[86],"CIPER":[87,106],"(Cross-view":[88],"Image-retrieval":[89],"Pose-estimation":[91],"transformER),":[92],"single":[94],"architecture":[95],"that":[96,142],"jointly":[97],"performs":[98],"both":[99],"tasks":[100],"mutually":[102],"beneficial":[103],"learning.":[105],"uses":[107,143],"shared":[109],"transformer":[110,139],"encoder":[111],"with":[112],"task-specific":[113],"tokens":[114],"to":[115],"disentangle":[116],"global":[117],"features":[119,145],"from":[120],"spatial":[121,147],"cues.":[123],"To":[124],"bridge":[125],"large":[127],"domain":[128],"gap":[129],"between":[130],"views,":[134],"we":[135],"introduce":[136],"two-way":[138],"decoder":[141],"queries":[148],"for":[149],"bidirectional":[150],"cross-attention.":[151],"A":[152],"set":[153],"prediction":[154],"strategy":[155],"further":[156],"enables":[157],"stable":[158],"regression":[160],"under":[161,177],"multi-task":[164],"objective.":[165],"Experiments":[166],"on":[167],"VIGOR,":[168],"KITTI,":[169],"Ford":[171],"Multi-AV":[172],"demonstrate":[173],"competitive":[174],"performance,":[175],"especially":[176],"limited":[178],"field-of-view":[179],"arbitrary":[181],"orientation":[182],"conditions.":[183],"Code":[184],"is":[185],"available":[186],"https://github.com/yurimjeon1892/CIPER.":[188]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-05T00:00:00"}