{"id":"https://openalex.org/W4386907270","doi":"https://doi.org/10.48550/arxiv.2309.10091","title":"Unified Coarse-to-Fine Alignment for Video-Text Retrieval","display_name":"Unified Coarse-to-Fine Alignment for Video-Text Retrieval","publication_year":2023,"publication_date":"2023-09-18","ids":{"openalex":"https://openalex.org/W4386907270","doi":"https://doi.org/10.48550/arxiv.2309.10091"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2309.10091","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.10091","pdf_url":"https://arxiv.org/pdf/2309.10091","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2309.10091","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022165659","display_name":"Ziyang Wang","orcid":"https://orcid.org/0000-0002-0368-9590"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ziyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079882340","display_name":"Yi-Lin Sung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sung, Yi-Lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657102","display_name":"Feng Cheng","orcid":"https://orcid.org/0000-0002-0148-7311"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081800468","display_name":"Gedas Bertasius","orcid":"https://orcid.org/0000-0003-1800-4790"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bertasius, Gedas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5001987532","display_name":"Mohit Bansal","orcid":"https://orcid.org/0000-0001-5522-1351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bansal, Mohit","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":true,"cited_by_count":2,"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9968000054359436,"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/granularity","display_name":"Granularity","score":0.8727325201034546},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8311761021614075},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6665682196617126},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6097134351730347},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5411028861999512},{"id":"https://openalex.org/keywords/video-retrieval","display_name":"Video retrieval","score":0.505500078201294},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4976952373981476},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.474606454372406},{"id":"https://openalex.org/keywords/unification","display_name":"Unification","score":0.47313275933265686},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4698304831981659},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4244760572910309},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37105539441108704},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27502381801605225}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.8727325201034546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8311761021614075},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6665682196617126},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6097134351730347},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5411028861999512},{"id":"https://openalex.org/C2983174267","wikidata":"https://www.wikidata.org/wiki/Q3775098","display_name":"Video retrieval","level":2,"score":0.505500078201294},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4976952373981476},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.474606454372406},{"id":"https://openalex.org/C96146094","wikidata":"https://www.wikidata.org/wiki/Q609057","display_name":"Unification","level":2,"score":0.47313275933265686},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4698304831981659},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4244760572910309},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37105539441108704},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27502381801605225},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2309.10091","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.10091","pdf_url":"https://arxiv.org/pdf/2309.10091","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":null},{"id":"doi:10.48550/arxiv.2309.10091","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2309.10091","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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:2309.10091","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.10091","pdf_url":"https://arxiv.org/pdf/2309.10091","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G1472423617","display_name":null,"funder_award_id":"FA8750-19-2-1004","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G2921176242","display_name":null,"funder_award_id":"W911NF2110220","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G527861410","display_name":null,"funder_award_id":"DRL211263","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5599941371","display_name":null,"funder_award_id":"N00014-23-1-2356","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320310013","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386907270.pdf","grobid_xml":"https://content.openalex.org/works/W4386907270.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2367630557","https://openalex.org/W101666983","https://openalex.org/W2931688134","https://openalex.org/W2183792531","https://openalex.org/W2377919138","https://openalex.org/W2595286499","https://openalex.org/W2794344379","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678"],"abstract_inverted_index":{"The":[0],"canonical":[1],"approach":[2],"to":[3,23,35,50,95,108,122],"video-text":[4,166],"retrieval":[5,167,177],"leverages":[6],"a":[7,59,110],"coarse-grained":[8],"or":[9],"fine-grained":[10],"alignment":[11],"between":[12],"visual":[13,44,84,101],"and":[14,41,46,134,172,182],"textual":[15],"information.":[16],"However,":[17],"retrieving":[18],"the":[19,24,33,51,70,80,97,105,119,124,143,151],"correct":[20],"video":[21],"according":[22],"text":[25,52],"query":[26],"is":[27,187],"often":[28],"challenging":[29],"as":[30],"it":[31],"requires":[32],"ability":[34],"reason":[36],"about":[37],"both":[38],"high-level":[39],"(scene)":[40],"low-level":[42],"(object)":[43],"clues":[45],"how":[47],"they":[48],"relate":[49],"query.":[53],"To":[54,78],"this":[55],"end,":[56],"we":[57,86,117],"propose":[58],"Unified":[60],"Coarse-to-fine":[61],"Alignment":[62],"model,":[63],"dubbed":[64],"UCoFiA.":[65],"Specifically,":[66],"our":[67],"model":[68],"captures":[69],"cross-modal":[71,106],"similarity":[72,107,111,145],"information":[73],"at":[74,137,190],"different":[75,100,138,147],"granularity":[76],"levels.":[77,139],"alleviate":[79],"effect":[81],"of":[82,99,126,146,154],"irrelevant":[83],"clues,":[85],"also":[87],"apply":[88,118],"an":[89],"Interactive":[90],"Similarity":[91],"Aggregation":[92],"module":[93],"(ISA)":[94],"consider":[96],"importance":[98],"features":[102],"while":[103],"aggregating":[104],"obtain":[109],"score":[112],"for":[113],"each":[114,127],"granularity.":[115],"Finally,":[116],"Sinkhorn-Knopp":[120],"algorithm":[121],"normalize":[123],"similarities":[125],"level":[128],"before":[129],"summing":[130],"them,":[131],"alleviating":[132],"over-":[133],"under-representation":[135],"issues":[136],"By":[140],"jointly":[141],"considering":[142],"crossmodal":[144],"granularity,":[148],"UCoFiA":[149,158],"allows":[150],"effective":[152],"unification":[153],"multi-grained":[155],"alignments.":[156],"Empirically,":[157],"outperforms":[159],"previous":[160],"state-of-the-art":[161],"CLIP-based":[162],"methods":[163],"on":[164,179],"multiple":[165],"benchmarks,":[168],"achieving":[169],"2.4%,":[170],"1.4%":[171],"1.3%":[173],"improvements":[174],"in":[175],"text-to-video":[176],"R@1":[178],"MSR-VTT,":[180],"Activity-Net,":[181],"DiDeMo,":[183],"respectively.":[184],"Our":[185],"code":[186],"publicly":[188],"available":[189],"https://github.com/Ziyang412/UCoFiA.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
