{"id":"https://openalex.org/W7166704578","doi":"https://doi.org/10.48550/arxiv.2606.28920","title":"ExACT: Exemplar-Driven Calibrated Refinement for Training-Free Visual Grounding in Remote Sensing Images","display_name":"ExACT: Exemplar-Driven Calibrated Refinement for Training-Free Visual Grounding in Remote Sensing Images","publication_year":2026,"publication_date":"2026-06-27","ids":{"openalex":"https://openalex.org/W7166704578","doi":"https://doi.org/10.48550/arxiv.2606.28920"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.28920","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28920","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.28920","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083233746","display_name":"Zixiao Zhang","orcid":"https://orcid.org/0000-0001-7404-4573"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zixiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139704187","display_name":"Lingling Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Lingling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139696396","display_name":"Pei He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Pei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139658000","display_name":"Xu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139642984","display_name":"Licheng Jiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiao, Licheng","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.5202999711036682,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.5202999711036682,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.13199999928474426,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.10270000249147415,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/discriminative-model","display_name":"Discriminative model","score":0.6068000197410583},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.59579998254776},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5270000100135803},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.48820000886917114},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.43869999051094055},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.37700000405311584},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3598000109195709},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3262999951839447}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7602999806404114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.710099995136261},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6068000197410583},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6011999845504761},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.59579998254776},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5270000100135803},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.48820000886917114},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.2996000051498413},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.29490000009536743},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.27720001339912415},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C2780527621","wikidata":"https://www.wikidata.org/wiki/Q7936593","display_name":"Visual control","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.28920","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28920","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.28920","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28920","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"score":0.7025027275085449,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Remote":[0],"sensing":[1],"visual":[2,50,81,105],"grounding":[3],"(RSVG)":[4],"aims":[5],"to":[6,84,111,140,161],"locate":[7],"specific":[8],"objects":[9],"in":[10,22],"high-resolution":[11],"RS":[12,54],"imagery":[13],"using":[14],"free-form":[15],"natural":[16],"language":[17,25],"descriptions.":[18],"While":[19],"recent":[20],"advances":[21],"multimodal":[23],"large":[24],"models":[26],"(MLLMs)":[27],"show":[28],"great":[29],"potential":[30],"for":[31,90],"such":[32],"open-vocabulary":[33],"RSVG,":[34],"their":[35],"training-free":[36,75,175],"adaptation":[37],"is":[38],"hindered":[39],"by":[40,78],"the":[41,108,113,142,156,169],"modality":[42],"gap":[43,57],"between":[44],"abstract":[45],"linguistic":[46],"semantics":[47],"and":[48,124,148,176],"fine-grained":[49,104],"cues.":[51],"In":[52],"cluttered":[53],"scenes,":[55],"this":[56,65],"inevitably":[58],"causes":[59],"severe":[60],"localization":[61],"drift.":[62],"To":[63],"bridge":[64],"gap,":[66],"we":[67,95],"propose":[68,96],"Exemplar-driven":[69],"Calibrated":[70],"Refinement":[71],"(ExACT),":[72],"a":[73,79,97,130],"novel":[74],"framework":[76],"driven":[77],"one-shot":[80],"prompting":[82],"mechanism":[83],"explicitly":[85],"provide":[86],"discriminative":[87],"structural":[88],"guidance":[89],"precise":[91,163],"pixel-level":[92,164],"localization.":[93],"Specifically,":[94],"Vision":[98],"Exemplar-based":[99],"Calibrator":[100],"(VEC)":[101],"that":[102],"extracts":[103],"correspondences":[106],"from":[107,117],"given":[109],"exemplar":[110],"rectify":[112],"rough":[114],"cross-modal":[115],"priors":[116,144],"frozen":[118],"MLLMs,":[119],"effectively":[120],"suppressing":[121],"background":[122],"artifacts":[123],"accurately":[125],"outlining":[126],"target":[127],"boundaries.":[128],"Subsequently,":[129],"Structure-Aware":[131],"Refiner":[132],"(SAR)":[133],"employs":[134],"an":[135],"iterative":[136],"merge-and-select":[137],"clustering":[138],"strategy":[139],"consolidate":[141],"calibrated":[143],"into":[145],"high-quality":[146],"positive":[147],"negative":[149],"geometric":[150],"prompts.":[151],"These":[152],"prompts":[153],"then":[154],"guide":[155],"Segment":[157],"Anything":[158],"Model":[159],"(SAM)":[160],"achieve":[162],"predictions.":[165],"Extensive":[166],"experiments":[167],"confirm":[168],"superiority":[170],"of":[171],"ExACT":[172],"over":[173],"existing":[174],"weakly-supervised":[177],"methods.":[178]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-01T00:00:00"}
