{"id":"https://openalex.org/W3170097241","doi":"https://doi.org/10.1109/cbmi50038.2021.9461890","title":"Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features","display_name":"Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features","publication_year":2021,"publication_date":"2021-06-24","ids":{"openalex":"https://openalex.org/W3170097241","doi":"https://doi.org/10.1109/cbmi50038.2021.9461890","mag":"3170097241"},"language":"en","primary_location":{"id":"doi:10.1109/cbmi50038.2021.9461890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbmi50038.2021.9461890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Content-Based Multimedia Indexing (CBMI)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2106.00358","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007125882","display_name":"Nicola Messina","orcid":"https://orcid.org/0000-0003-3011-2487"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicola Messina","raw_affiliation_strings":["Institute of Information Science and Technologies, National Research Council, Pisa, Italy","National Research Council,Institute of Information Science and Technologies,Pisa,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science and Technologies, National Research Council, Pisa, Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"raw_affiliation_string":"National Research Council,Institute of Information Science and Technologies,Pisa,Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072396889","display_name":"Giuseppe Amato","orcid":"https://orcid.org/0000-0003-0171-4315"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe Amato","raw_affiliation_strings":["Institute of Information Science and Technologies, National Research Council, Pisa, Italy","National Research Council,Institute of Information Science and Technologies,Pisa,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science and Technologies, National Research Council, Pisa, Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"raw_affiliation_string":"National Research Council,Institute of Information Science and Technologies,Pisa,Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047189288","display_name":"Fabrizio Falchi","orcid":"https://orcid.org/0000-0001-6258-5313"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabrizio Falchi","raw_affiliation_strings":["Institute of Information Science and Technologies, National Research Council, Pisa, Italy","National Research Council,Institute of Information Science and Technologies,Pisa,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science and Technologies, National Research Council, Pisa, Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"raw_affiliation_string":"National Research Council,Institute of Information Science and Technologies,Pisa,Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072879702","display_name":"Claudio Gennaro","orcid":"https://orcid.org/0000-0002-3715-149X"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Claudio Gennaro","raw_affiliation_strings":["Institute of Information Science and Technologies, National Research Council, Pisa, Italy","National Research Council,Institute of Information Science and Technologies,Pisa,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science and Technologies, National Research Council, Pisa, Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]},{"raw_affiliation_string":"National Research Council,Institute of Information Science and Technologies,Pisa,Italy","institution_ids":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061688822","display_name":"St\u00e9phane Marchand\u2010Maillet","orcid":"https://orcid.org/0000-0002-4875-6101"},"institutions":[{"id":"https://openalex.org/I114457229","display_name":"University of Geneva","ror":"https://ror.org/01swzsf04","country_code":"CH","type":"education","lineage":["https://openalex.org/I114457229"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Stephane Marchand-Maillet","raw_affiliation_strings":["University of Geneva, Geneva, Switzerland","University of Geneva , Geneva, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Geneva, Geneva, Switzerland","institution_ids":["https://openalex.org/I114457229"]},{"raw_affiliation_string":"University of Geneva , Geneva, Switzerland","institution_ids":["https://openalex.org/I114457229"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0955,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.32472054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9990000128746033,"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":0.9916999936103821,"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/computer-science","display_name":"Computer science","score":0.8064127564430237},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6585652828216553},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6101130247116089},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.5054991245269775},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.4910423755645752},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.4552116096019745},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.4388084411621094},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4204446077346802},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.419005423784256},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4166010022163391},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37232333421707153},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3670389652252197},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30937328934669495}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8064127564430237},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6585652828216553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6101130247116089},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.5054991245269775},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.4910423755645752},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.4552116096019745},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.4388084411621094},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4204446077346802},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.419005423784256},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4166010022163391},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37232333421707153},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3670389652252197},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30937328934669495},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cbmi50038.2021.9461890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbmi50038.2021.9461890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Content-Based Multimedia Indexing (CBMI)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2106.00358","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.00358","pdf_url":"https://arxiv.org/pdf/2106.00358","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3170097241","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2106.00358.pdf","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2106.00358","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2106.00358","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":"pmh:oai:arXiv.org:2106.00358","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.00358","pdf_url":"https://arxiv.org/pdf/2106.00358","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.800000011920929,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1905882502","https://openalex.org/W2033885323","https://openalex.org/W2062118960","https://openalex.org/W2088866137","https://openalex.org/W2131846894","https://openalex.org/W2155541015","https://openalex.org/W2174726731","https://openalex.org/W2467557055","https://openalex.org/W2522145079","https://openalex.org/W2745461083","https://openalex.org/W2807884750","https://openalex.org/W2962849264","https://openalex.org/W2962964995","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963499204","https://openalex.org/W2970608575","https://openalex.org/W2970717081","https://openalex.org/W2973978812","https://openalex.org/W2988823324","https://openalex.org/W3016333779","https://openalex.org/W3104180728","https://openalex.org/W6630875275","https://openalex.org/W6682778277","https://openalex.org/W6685522000","https://openalex.org/W6739901393","https://openalex.org/W6747225742","https://openalex.org/W6755207826","https://openalex.org/W6766904570","https://openalex.org/W6767617715","https://openalex.org/W6776031226"],"related_works":["https://openalex.org/W3173291851","https://openalex.org/W2783179304","https://openalex.org/W3048782180","https://openalex.org/W2883791312","https://openalex.org/W3044757136","https://openalex.org/W3025923720","https://openalex.org/W3206569427","https://openalex.org/W1538243752","https://openalex.org/W2315835051","https://openalex.org/W2132948246","https://openalex.org/W2085272267","https://openalex.org/W2294699487","https://openalex.org/W2006385008","https://openalex.org/W3203247393","https://openalex.org/W2949436286","https://openalex.org/W2419728325","https://openalex.org/W170198589","https://openalex.org/W3193486900","https://openalex.org/W2017628470","https://openalex.org/W3062155679"],"abstract_inverted_index":{"Cross-modal":[0],"retrieval":[1,35,89],"is":[2,40,139,165],"an":[3,106,160],"important":[4,232],"functionality":[5],"in":[6,230],"modern":[7],"search":[8],"engines,":[9],"as":[10,159,177,179],"it":[11],"increases":[12],"the":[13,33,38,52,64,68,84,88,96,143,154,186,191,206,212,223],"user":[14],"experience":[15],"by":[16,91,205],"allowing":[17],"queries":[18],"and":[19,79,175,196,226],"retrieved":[20],"objects":[21],"to":[22,24,41,121,140,209],"pertain":[23],"different":[25,118],"modalities.":[26],"In":[27,113],"this":[28,114,231],"paper,":[29],"we":[30,116],"focus":[31],"on":[32,67,87,222],"image-sentence":[34,69,161],"task,":[36],"where":[37],"objective":[39,138],"efficiently":[42],"find":[43],"relevant":[44,53],"images":[45,110,174],"for":[46,55,133,145,167],"a":[47,56],"given":[48,57],"sentence":[49,197],"(image-retrieval)":[50],"or":[51,111],"sentences":[54],"image":[58],"(sentence-retrieval).":[59],"Computer":[60],"vision":[61],"literature":[62],"reports":[63],"best":[65],"results":[66,221],"matching":[70,85],"task":[71,90],"using":[72],"deep":[73,124],"neural":[74],"networks":[75],"equipped":[76],"with":[77,105],"attention":[78],"self-attention":[80],"mechanisms.":[81],"They":[82],"evaluate":[83],"performance":[86],"performing":[92],"sequential":[93],"scans":[94],"of":[95,109,148,182,190],"whole":[97,173],"dataset.":[98],"This":[99],"method":[100],"does":[101],"not":[102],"scale":[103],"well":[104,178],"increasing":[107],"amount":[108],"captions.":[112],"work,":[115],"explore":[117],"preprocessing":[119],"techniques":[120],"produce":[122],"sparsified":[123],"multi-modal":[125,150],"features":[126,162],"extracting":[127],"them":[128],"from":[129],"state-of-the-art":[130],"deep-learning":[131],"architectures":[132],"image-text":[134],"matching.":[135],"Our":[136,216],"main":[137],"lay":[141],"down":[142],"paths":[144],"efficient":[146],"indexing":[147],"complex":[149],"descriptions.":[151],"We":[152],"use":[153],"recently":[155],"introduced":[156],"TERN":[157,207],"architecture":[158],"extractor.":[163],"It":[164],"designed":[166],"producing":[168],"fixed-size":[169],"1024-d":[170,183],"vectors":[171,184,202],"describing":[172,185],"sentences,":[176],"variable-length":[180],"sets":[181],"various":[187],"building":[188],"components":[189],"two":[192],"modalities":[193],"(image":[194],"regions":[195],"words":[198],"respectively).":[199],"All":[200],"these":[201],"are":[203],"enforced":[204],"design":[208],"lie":[210],"into":[211],"same":[213],"common":[214],"space.":[215],"experiments":[217],"show":[218],"interesting":[219],"preliminary":[220],"explored":[224],"methods":[225],"suggest":[227],"further":[228],"experimentation":[229],"research":[233],"direction.":[234]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}