{"id":"https://openalex.org/W4414360001","doi":"https://doi.org/10.24963/ijcai.2025/174","title":"Language-Guided Hybrid Representation Learning for Visual Grounding on Remote Sensing Images","display_name":"Language-Guided Hybrid Representation Learning for Visual Grounding on Remote Sensing Images","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360001","doi":"https://doi.org/10.24963/ijcai.2025/174"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/174","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/174","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":"https://openalex.org/A5100686120","display_name":"Biao Liu","orcid":"https://orcid.org/0000-0002-9373-4948"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Biao Liu","raw_affiliation_strings":["Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100331674","display_name":"Xu Liu","orcid":"https://orcid.org/0000-0001-8650-5816"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Liu","raw_affiliation_strings":["Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110654179","display_name":"Lingling Li","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingling Li","raw_affiliation_strings":["Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","orcid":"https://orcid.org/0000-0003-3354-9617"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licheng Jiao","raw_affiliation_strings":["Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100453075","display_name":"Fang Liu","orcid":"https://orcid.org/0000-0002-5669-9354"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Liu","raw_affiliation_strings":["Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101280318","display_name":"Xinyu Sun","orcid":"https://orcid.org/0009-0005-6223-0287"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Sun","raw_affiliation_strings":["Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081369135","display_name":"Yongli Huang","orcid":"https://orcid.org/0000-0002-6250-7056"},"institutions":[{"id":"https://openalex.org/I13985625","display_name":"East China Jiaotong University","ror":"https://ror.org/05x2f1m38","country_code":"CN","type":"education","lineage":["https://openalex.org/I13985625"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youlin Huang","raw_affiliation_strings":["East China Jiaotong University"],"affiliations":[{"raw_affiliation_string":"East China Jiaotong University","institution_ids":["https://openalex.org/I13985625"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100686120"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26724629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1557","last_page":"1566"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9891999959945679,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9891999959945679,"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":0.9882000088691711,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9690999984741211,"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/embedding","display_name":"Embedding","score":0.5203999876976013},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.47279998660087585},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.47200000286102295},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44589999318122864},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4221000075340271},{"id":"https://openalex.org/keywords/ground","display_name":"Ground","score":0.4092000126838684},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.39820000529289246},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.38690000772476196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7444999814033508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6643999814987183},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5203999876976013},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4916999936103821},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.47279998660087585},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.47200000286102295},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44589999318122864},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4221000075340271},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.4092000126838684},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.39820000529289246},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3790999948978424},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.36579999327659607},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3650999963283539},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33820000290870667},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3352000117301941},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.32019999623298645},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.26350000500679016},{"id":"https://openalex.org/C2780103172","wikidata":"https://www.wikidata.org/wiki/Q1309721","display_name":"Visual Objects","level":3,"score":0.26269999146461487}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/174","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/174","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":{"Visual":[0],"grounding":[1,33,58],"(VG)":[2],"refers":[3],"to":[4,98,118,137,161,187],"detecting":[5],"the":[6,21,40,77,100,105,110,120,139,142,154,166,173,177,183,191],"specific":[7],"objects":[8],"in":[9,20],"images":[10],"based":[11],"on":[12,190],"linguistic":[13,159],"expressions,":[14],"and":[15,43,88,145,148,169,193],"it":[16],"has":[17],"profound":[18],"significance":[19],"advanced":[22],"interpretation":[23],"of":[24,141],"natural":[25],"images.":[26],"In":[27],"remote":[28,55],"sensing":[29,56],"image":[30],"interpretation,":[31],"visual":[32,57,89,146,163,167],"is":[34,113,135],"limited":[35],"by":[36,115],"characteristics":[37],"such":[38],"as":[39,91,165,172],"complex":[41],"scenes":[42],"diverse":[44],"object":[45,122],"sizes.":[46],"To":[47],"solve":[48],"this":[49],"problem,":[50],"we":[51,69,157,180],"propose":[52],"a":[53,71,128],"novel":[54],"(RSVG)":[59],"framework,":[60],"named":[61],"language-guided":[62],"hybrid":[63,92,116,155],"representation":[64],"learning":[65],"Transformer":[66,74],"(LGFormer).":[67],"Specifically,":[68],"designed":[70,136,181],"multimodal":[72,79],"dual-encoder":[73],"structure":[75,84],"called":[76],"adaptive":[78],"feature":[80,131],"fusion":[81],"module.":[82],"This":[83],"innovatively":[85],"integrates":[86],"text":[87,144],"features":[90,147,164,171],"queries,":[93,156],"enabling":[94],"early-stage":[95],"decoding":[96],"queries":[97,117],"perceive":[99],"target":[101],"position":[102],"accurately.":[103],"Then,":[104],"different":[106],"modal":[107],"information":[108],"from":[109],"dual":[111],"encoders":[112],"aggregated":[114],"obtain":[119],"final":[121],"embedding":[123],"for":[124,153],"coordinate":[125],"regression.":[126],"Besides,":[127],"multi-scale":[129],"cross-modal":[130],"enhancement":[132],"module":[133],"(MSCM)":[134],"enhance":[138],"self-representation":[140],"extracted":[143],"align":[149],"them":[150],"semantically.":[151],"As":[152],"use":[158],"guidance":[160],"select":[162],"part":[168],"sentence-level":[170],"textual":[174],"part.":[175],"Finally,":[176],"LGFormer":[178],"model":[179],"achieved":[182],"best":[184],"results":[185],"compared":[186],"existing":[188],"models":[189],"DIOR-RSVG":[192],"OPT-RSVG":[194],"datasets.":[195]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
