{"id":"https://openalex.org/W4403791994","doi":"https://doi.org/10.1145/3664647.3681280","title":"Accurate and Lightweight Learning for Specific Domain Image-Text Retrieval","display_name":"Accurate and Lightweight Learning for Specific Domain Image-Text Retrieval","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403791994","doi":"https://doi.org/10.1145/3664647.3681280"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681280","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681280","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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/A5039983188","display_name":"Rui Yang","orcid":"https://orcid.org/0000-0002-3209-0456"},"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":"Rui Yang","raw_affiliation_strings":["Xidian University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065660222","display_name":"Shuang Wang","orcid":"https://orcid.org/0000-0003-4940-1211"},"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":"Shuang Wang","raw_affiliation_strings":["Xidian University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025422800","display_name":"Jianwei Tao","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":"Jianwei Tao","raw_affiliation_strings":["Xidian University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110979085","display_name":"Yingping Han","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":"Yingping Han","raw_affiliation_strings":["Xidian University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053391771","display_name":"Qiaoling Lin","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":"Qiaoling Lin","raw_affiliation_strings":["Xidian University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040240404","display_name":"Yanhe Guo","orcid":"https://orcid.org/0009-0003-6144-5070"},"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":"YanHe Guo","raw_affiliation_strings":["Xidian University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043022387","display_name":"Biao Hou","orcid":"https://orcid.org/0000-0002-1996-186X"},"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":"Biao Hou","raw_affiliation_strings":["Xidian University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","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":"Licheng Jiao","raw_affiliation_strings":["Xidian University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5039983188"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":1.2464,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81409316,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"9719","last_page":"9728"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987000226974487,"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/computer-science","display_name":"Computer science","score":0.7708644270896912},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5292512774467468},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.520839512348175},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49729493260383606},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4664340317249298},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.446074515581131},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4226524233818054},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35641515254974365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06348401308059692}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7708644270896912},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5292512774467468},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.520839512348175},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49729493260383606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4664340317249298},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.446074515581131},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4226524233818054},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35641515254974365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06348401308059692},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3681280","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681280","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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":65,"referenced_works":["https://openalex.org/W1905882502","https://openalex.org/W2510520237","https://openalex.org/W2779054585","https://openalex.org/W2801814609","https://openalex.org/W2883311563","https://openalex.org/W2894786240","https://openalex.org/W2954054736","https://openalex.org/W2962964995","https://openalex.org/W2963449390","https://openalex.org/W2963882743","https://openalex.org/W2985951359","https://openalex.org/W2994818707","https://openalex.org/W2997421053","https://openalex.org/W2997666887","https://openalex.org/W2998356391","https://openalex.org/W3002332355","https://openalex.org/W3015686580","https://openalex.org/W3035454331","https://openalex.org/W3035524453","https://openalex.org/W3082913072","https://openalex.org/W3092820619","https://openalex.org/W3093025987","https://openalex.org/W3100245404","https://openalex.org/W3138516171","https://openalex.org/W3140792177","https://openalex.org/W3157986864","https://openalex.org/W3165084071","https://openalex.org/W3171668871","https://openalex.org/W3198377975","https://openalex.org/W3198659451","https://openalex.org/W3206868111","https://openalex.org/W3208803664","https://openalex.org/W4224911357","https://openalex.org/W4225159440","https://openalex.org/W4226172762","https://openalex.org/W4249138131","https://openalex.org/W4289538158","https://openalex.org/W4297833440","https://openalex.org/W4304098245","https://openalex.org/W4308743547","https://openalex.org/W4312272363","https://openalex.org/W4312651322","https://openalex.org/W4313121711","https://openalex.org/W4322730934","https://openalex.org/W4375928712","https://openalex.org/W4379806246","https://openalex.org/W4386065462","https://openalex.org/W4386071547","https://openalex.org/W4386076131","https://openalex.org/W4386076289","https://openalex.org/W4386076503","https://openalex.org/W4386212341","https://openalex.org/W4386758381","https://openalex.org/W4386952228","https://openalex.org/W4387802324","https://openalex.org/W4387968073","https://openalex.org/W4387969154","https://openalex.org/W4387969378","https://openalex.org/W4388145471","https://openalex.org/W4388740367","https://openalex.org/W4390754261","https://openalex.org/W4390872645","https://openalex.org/W4390872745","https://openalex.org/W4390874394","https://openalex.org/W4403295410"],"related_works":["https://openalex.org/W2087793626","https://openalex.org/W2755342338","https://openalex.org/W2779427294","https://openalex.org/W2052697133","https://openalex.org/W2775347418","https://openalex.org/W2625805835","https://openalex.org/W2079911747","https://openalex.org/W3116076068","https://openalex.org/W2990774877","https://openalex.org/W3093339210"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,178],"vision-language":[3],"pre-trained":[4],"models":[5],"like":[6],"CLIP":[7,26,157],"have":[8],"greatly":[9],"enhanced":[10],"general":[11],"domain":[12,91],"image-text":[13],"retrieval":[14,64,117,137],"performance.":[15],"This":[16],"success":[17],"has":[18],"led":[19],"scholars":[20],"to":[21,27,115,140,151,158],"develop":[22],"methods":[23,48],"for":[24,49,89,167],"applying":[25],"Specific":[28],"Domain":[29],"Image-Text":[30,38],"Retrieval":[31,39,93],"(SDITR)":[32],"tasks":[33],"such":[34],"as":[35],"Remote":[36],"Sensing":[37],"(RSITR)":[40],"and":[41,66,86,109,119,132,180,197],"Text-Image":[42],"Person":[43],"Re-identification":[44],"(TIReID).":[45],"However,":[46],"these":[47,77],"SDITR":[50],"often":[51],"neglect":[52],"two":[53],"critical":[54],"aspects:":[55],"the":[56,63,67,97,126,141,164],"enhancement":[57],"of":[58,69],"modal-level":[59],"distribution":[60,103],"consistency":[61],"within":[62,130],"space":[65,138],"reduction":[68],"CLIP's":[70],"computational":[71,120,198],"cost":[72],"during":[73,200],"inference.":[74],"To":[75],"address":[76],"issues,":[78],"this":[79],"paper":[80],"presents":[81],"a":[82,101,110,136,146,159,192],"novel":[83],"framework,":[84],"Accurate":[85],"lightweight":[87],"learning":[88],"specific":[90],"Image-text":[92],"(AIR),":[94],"based":[95],"on":[96],"CLIP.":[98],"AIR":[99],"incorporates":[100],"Modal-Level":[102],"Consistency":[104],"Enhancement":[105],"regularization":[106],"(MLCE)":[107],"loss":[108,124,185],"Self-Pruning":[111],"Distillation":[112],"Strategy":[113],"(SPDS)":[114],"improve":[116],"precision":[118],"efficiency.":[121],"The":[122],"MLCE":[123,184],"harmonizes":[125],"sample":[127],"distance":[128],"distributions":[129],"image":[131],"text":[133],"modalities,":[134],"fostering":[135],"closer":[139],"ideal":[142],"state.":[143],"SPDS":[144,190],"employs":[145],"strategic":[147],"knowledge":[148],"distillation":[149],"process":[150],"transfer":[152],"deep":[153],"multimodal":[154],"insights":[155],"from":[156],"shallower":[160],"level,":[161],"maintaining":[162],"only":[163],"essential":[165],"layers":[166],"inference,":[168],"thus":[169],"achieving":[170],"model":[171],"light-weighting.":[172],"Comprehensive":[173],"experiments":[174],"across":[175],"various":[176],"datasets":[177],"RSITR":[179],"TIReID":[181],"reveal":[182],"that":[183],"secures":[186],"optimal":[187],"retrieval,":[188],"while":[189],"achieves":[191],"favorable":[193],"balance":[194],"between":[195],"accuracy":[196],"demand":[199],"testing.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}