{"id":"https://openalex.org/W4402260221","doi":"https://doi.org/10.1109/igarss53475.2024.10640383","title":"From Coarse To Fine: An Offline-Online Approach for Remote Sensing Cross-Modal Retrieval","display_name":"From Coarse To Fine: An Offline-Online Approach for Remote Sensing Cross-Modal Retrieval","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402260221","doi":"https://doi.org/10.1109/igarss53475.2024.10640383"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10640383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10640383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5035744787","display_name":"Wenqian Zhou","orcid":"https://orcid.org/0009-0001-1190-0077"},"institutions":[{"id":"https://openalex.org/I109173049","display_name":"Beijing Foreign Studies University","ror":"https://ror.org/00jdr0662","country_code":"CN","type":"education","lineage":["https://openalex.org/I109173049"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqian Zhou","raw_affiliation_strings":["School of Information Science and Technology Beijing Foreign Studies University,Beijing,China,100089"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology Beijing Foreign Studies University,Beijing,China,100089","institution_ids":["https://openalex.org/I109173049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067703101","display_name":"Hanlin Wu","orcid":"https://orcid.org/0000-0002-3505-0521"},"institutions":[{"id":"https://openalex.org/I109173049","display_name":"Beijing Foreign Studies University","ror":"https://ror.org/00jdr0662","country_code":"CN","type":"education","lineage":["https://openalex.org/I109173049"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanlin Wu","raw_affiliation_strings":["School of Information Science and Technology Beijing Foreign Studies University,Beijing,China,100089"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology Beijing Foreign Studies University,Beijing,China,100089","institution_ids":["https://openalex.org/I109173049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I109173049"],"apc_list":null,"apc_paid":null,"fwci":0.2629,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53191987,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"305","last_page":"309"},"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":0.9958999752998352,"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":0.9958999752998352,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9850999712944031,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9764000177383423,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.7757856845855713},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7222560048103333},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.49401456117630005},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34691500663757324},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3337398171424866},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1296609342098236},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.05717068910598755}],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7757856845855713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7222560048103333},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.49401456117630005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34691500663757324},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3337398171424866},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1296609342098236},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.05717068910598755},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10640383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10640383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2779054585","https://openalex.org/W3090449556","https://openalex.org/W3094502228","https://openalex.org/W3100245404","https://openalex.org/W3165084071","https://openalex.org/W3193402170","https://openalex.org/W3208803664","https://openalex.org/W4224911357","https://openalex.org/W4226172762","https://openalex.org/W4313055764","https://openalex.org/W4378696930","https://openalex.org/W4386212341","https://openalex.org/W4386952228","https://openalex.org/W4387969154","https://openalex.org/W6784333009","https://openalex.org/W6791353385","https://openalex.org/W6800139874"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"Remote":[0],"sensing":[1,13],"image-text":[2,67],"retrieval":[3,25,37,46,68,107],"(RSITR)":[4],"has":[5,34,43],"recently":[6],"attracted":[7],"unprecedented":[8],"attention":[9],"in":[10,48],"the":[11,45,71,91],"remote":[12],"(RS)":[14],"community.":[15],"Early":[16],"dual-stream":[17,78],"methods,":[18],"such":[19],"as":[20],"hash":[21],"retrieval,":[22],"offered":[23],"fast":[24],"speeds":[26],"but":[27],"suffered":[28],"from":[29],"low":[30],"accuracy.":[31],"Recent":[32],"research":[33],"markedly":[35],"improved":[36],"accuracy":[38],"through":[39],"single-stream":[40,98],"architectures,":[41],"yet":[42],"overlooked":[44],"efficiency":[47,57],"large-scale":[49],"RS":[50],"datasets.":[51],"To":[52,105],"achieve":[53],"a":[54,62,77,97],"balance":[55],"between":[56],"and":[58,113,118,125],"accuracy,":[59],"we":[60,75,95,109],"propose":[61],"coarse-to-fine":[63],"two-stage":[64],"framework":[65],"for":[66,84,121],"(C2F-ITR).":[69],"In":[70,90],"coarse":[72,123],"matching":[73,124],"stage,":[74,94],"employ":[76],"model":[79,99],"to":[80,100],"identify":[81],"candidate":[82,103],"results":[83],"an":[85],"image":[86,112],"or":[87],"text":[88,114],"query.":[89],"fine":[92,126],"reranking":[93,127],"use":[96],"rerank":[101],"these":[102],"results.":[104],"enhance":[106],"efficiency,":[108],"compute":[110],"all":[111],"embeddings":[115],"independently":[116],"offline":[117],"reuse":[119],"them":[120],"both":[122],"online.":[128],"Extensive":[129],"experiments":[130],"on":[131],"public":[132],"datasets":[133],"demonstrate":[134],"that":[135],"our":[136],"method":[137],"significantly":[138],"outperforms":[139],"existing":[140],"approaches.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}