{"id":"https://openalex.org/W4408345649","doi":"https://doi.org/10.1109/icassp49660.2025.10888058","title":"DLM-VMTL:A Double LayerMapper For Heterogeneous Data Video Multi-Task Prompt Learning","display_name":"DLM-VMTL:A Double LayerMapper For Heterogeneous Data Video Multi-Task Prompt Learning","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408345649","doi":"https://doi.org/10.1109/icassp49660.2025.10888058"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5111335454","display_name":"Zeyi Bo","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zeyi Bo","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,Harbin,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015900358","display_name":"Ye Jin","orcid":"https://orcid.org/0000-0002-8491-1391"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Jin","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,Harbin,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107406846","display_name":"Wuxi Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wuxi Sun","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,Harbin,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111335454"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01961265,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.98089998960495,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.98089998960495,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9750999808311462,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9476000070571899,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.776335597038269},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6463627815246582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41530683636665344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.776335597038269},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6463627815246582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41530683636665344},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":36,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W2031688197","https://openalex.org/W2099614498","https://openalex.org/W2109698606","https://openalex.org/W2117539524","https://openalex.org/W2126579184","https://openalex.org/W2336403884","https://openalex.org/W2549401308","https://openalex.org/W2618799552","https://openalex.org/W2625366777","https://openalex.org/W2964185501","https://openalex.org/W2982723417","https://openalex.org/W3012126539","https://openalex.org/W3198377975","https://openalex.org/W3206836360","https://openalex.org/W4297697565","https://openalex.org/W4312354469","https://openalex.org/W4312651322","https://openalex.org/W4313166855","https://openalex.org/W4386057769","https://openalex.org/W4390872309","https://openalex.org/W4390872502","https://openalex.org/W4390872626","https://openalex.org/W4390873360","https://openalex.org/W4394593151","https://openalex.org/W4402727550","https://openalex.org/W4402727714","https://openalex.org/W4402961794","https://openalex.org/W4411245031","https://openalex.org/W6739365718","https://openalex.org/W6739901393","https://openalex.org/W6759579507","https://openalex.org/W6776881853","https://openalex.org/W6791353385","https://openalex.org/W6838895014","https://openalex.org/W6857692509"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0,105],"recent":[1],"years,":[2],"the":[3,24,30,34,67,99,137,153],"parameters":[4],"of":[5,7,101,148],"backbones":[6],"Video":[8,25],"Understanding":[9],"tasks":[10,55,73,84,171],"continue":[11],"to":[12,41,45,52,98,119,135,151],"increase":[13],"and":[14,143,172],"even":[15],"reach":[16],"billion-level.":[17],"Whether":[18],"fine-tuning":[19],"a":[20,57,63,108,130],"specific":[21,35],"task":[22,65,150],"on":[23,166],"Foundation":[26],"Models(VFMs)":[27],"or":[28],"pre-training":[29],"model":[31],"designed":[32],"for":[33],"task,":[36],"incurs":[37],"significant":[38],"overhead.":[39],"How":[40],"enable":[42],"these":[43],"models":[44],"play":[46],"roles":[47],"other":[48,72],"than":[49,164],"those":[50],"corresponding":[51],"their":[53],"own":[54],"becomes":[56],"worthy":[58],"issue.":[59],"Multi-Task":[60],"Learning(MTL)":[61],"makes":[62],"visual":[64,141],"acquire":[66],"rich":[68],"shareable":[69,138],"knowledge":[70,139],"from":[71,125],"while":[74],"joint":[75],"training.":[76],"It":[77],"is":[78,91,117,133],"fully":[79],"explored":[80],"in":[81,94,127],"Image":[82],"Recognition":[83],"especially":[85],"dense":[86],"predict":[87],"tasks.":[88],"Nevertheless,":[89],"it":[90,126,145],"rarely":[92],"used":[93],"video":[95,103,111,169],"domain":[96],"due":[97],"lack":[100],"multi-labels":[102],"data.":[104],"this":[106],"paper,":[107],"heterogeneous":[109],"data":[110],"multi-task":[112],"prompt":[113],"learning":[114],"(VMTL)":[115],"method":[116],"proposed":[118,134],"address":[120],"above":[121],"problem.":[122],"It\u2019s":[123],"different":[124,168],"image":[128],"domain,":[129],"Double-Layers":[131],"Mapper(DLM)":[132],"extract":[136],"into":[140],"prompts":[142],"align":[144],"with":[146],"representation":[147],"primary":[149,154],"fine-tune":[152],"task.":[155],"Extensive":[156],"experiments":[157],"prove":[158],"that":[159],"our":[160],"DLM-VMTL":[161],"performs":[162],"better":[163],"baselines":[165],"6":[167],"understanding":[170],"11":[173],"datasets.":[174]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
