{"id":"https://openalex.org/W4397026326","doi":"https://doi.org/10.1109/tsmc.2024.3389672","title":"UNITE: Multitask Learning With Sufficient Feature for Dense Prediction","display_name":"UNITE: Multitask Learning With Sufficient Feature for Dense Prediction","publication_year":2024,"publication_date":"2024-05-17","ids":{"openalex":"https://openalex.org/W4397026326","doi":"https://doi.org/10.1109/tsmc.2024.3389672"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2024.3389672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2024.3389672","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-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/A5103250693","display_name":"Yuxin Tian","orcid":"https://orcid.org/0000-0003-3706-3462"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Tian","raw_affiliation_strings":["College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-3706-3462","affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039969889","display_name":"Yijie Lin","orcid":"https://orcid.org/0000-0003-1746-295X"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijie Lin","raw_affiliation_strings":["College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1746-295X","affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100347581","display_name":"Qing Ye","orcid":"https://orcid.org/0000-0003-3956-3348"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Ye","raw_affiliation_strings":["College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-3956-3348","affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370396","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-0579-3041"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022800038","display_name":"Xi Peng","orcid":"https://orcid.org/0000-0002-5727-2790"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Peng","raw_affiliation_strings":["College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-5727-2790","affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073535763","display_name":"Jiancheng Lv","orcid":"https://orcid.org/0000-0001-6551-3884"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiancheng Lv","raw_affiliation_strings":["College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-6551-3884","affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University and Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":1.445,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.83627968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"54","issue":"8","first_page":"5012","last_page":"5024"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9961000084877014,"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/leverage","display_name":"Leverage (statistics)","score":0.6215543746948242},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.6155754327774048},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6104536652565002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5047081708908081},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.44665783643722534},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4449910521507263},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4405684471130371},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41963309049606323}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6215543746948242},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.6155754327774048},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6104536652565002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5047081708908081},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.44665783643722534},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4449910521507263},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4405684471130371},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41963309049606323},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsmc.2024.3389672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2024.3389672","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3912052075","display_name":null,"funder_award_id":"2022YFN0017","funder_id":"https://openalex.org/F4320336596","funder_display_name":"Key Research and Development Program of Sichuan Province"},{"id":"https://openalex.org/G5382586338","display_name":null,"funder_award_id":"62106161","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6846722749","display_name":null,"funder_award_id":"61836006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7468431673","display_name":null,"funder_award_id":"2023YFG0278","funder_id":"https://openalex.org/F4320336596","funder_display_name":"Key Research and Development Program of Sichuan Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336596","display_name":"Key Research and Development Program of Sichuan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1614862348","https://openalex.org/W1849277567","https://openalex.org/W2031489346","https://openalex.org/W2097117768","https://openalex.org/W2100470808","https://openalex.org/W2125215748","https://openalex.org/W2162888803","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2549401308","https://openalex.org/W2562137921","https://openalex.org/W2589859332","https://openalex.org/W2593915460","https://openalex.org/W2624871570","https://openalex.org/W2783863635","https://openalex.org/W2798441115","https://openalex.org/W2890949887","https://openalex.org/W2903852246","https://openalex.org/W2906074946","https://openalex.org/W2943238452","https://openalex.org/W2950678851","https://openalex.org/W2959581809","https://openalex.org/W2962864421","https://openalex.org/W2963150697","https://openalex.org/W2963446712","https://openalex.org/W2963498646","https://openalex.org/W2963877604","https://openalex.org/W2964185501","https://openalex.org/W2964247799","https://openalex.org/W2966182616","https://openalex.org/W2982857584","https://openalex.org/W2994879149","https://openalex.org/W2998103904","https://openalex.org/W3010959250","https://openalex.org/W3014641072","https://openalex.org/W3034225195","https://openalex.org/W3034704453","https://openalex.org/W3080961686","https://openalex.org/W3085046840","https://openalex.org/W3096609285","https://openalex.org/W3097571420","https://openalex.org/W3101643310","https://openalex.org/W3105378872","https://openalex.org/W3134219938","https://openalex.org/W3143320354","https://openalex.org/W3176027594","https://openalex.org/W3183992282","https://openalex.org/W3204786153","https://openalex.org/W4303645333","https://openalex.org/W4319300305","https://openalex.org/W4382240142","https://openalex.org/W4383503846","https://openalex.org/W4385245566","https://openalex.org/W6675992320","https://openalex.org/W6679434410","https://openalex.org/W6690067395","https://openalex.org/W6734375575","https://openalex.org/W6738279954","https://openalex.org/W6739365718","https://openalex.org/W6745995898","https://openalex.org/W6745996482","https://openalex.org/W6761313651","https://openalex.org/W6763070779","https://openalex.org/W6770205404","https://openalex.org/W6771137081","https://openalex.org/W6779247072","https://openalex.org/W6782322686"],"related_works":["https://openalex.org/W2069133146","https://openalex.org/W1663079876","https://openalex.org/W2017545316","https://openalex.org/W2100576949","https://openalex.org/W2159686533","https://openalex.org/W4242339654","https://openalex.org/W2349160795","https://openalex.org/W2493838176","https://openalex.org/W4297686120","https://openalex.org/W2951720331"],"abstract_inverted_index":{"Existing":[0],"multitask":[1,147],"dense":[2],"prediction":[3],"methods":[4],"typically":[5],"rely":[6],"on":[7,109,133],"either":[8,23],"global":[9],"shared":[10],"neural":[11],"architecture":[12],"or":[13,27],"cross-task":[14,25,47,67,72,87],"fusion":[15],"strategy.":[16],"However,":[17],"these":[18],"approaches":[19],"tend":[20],"to":[21,44],"overlook":[22],"potential":[24],"complementary":[26,50,79],"consistent":[28,48,73,88],"information,":[29,51],"resulting":[30],"in":[31],"suboptimal":[32],"results.":[33],"Motivated":[34],"by":[35],"this":[36],"observation,":[37],"we":[38,64,84,142],"propose":[39],"a":[40,54,59,66],"novel":[41],"plug-and-play":[42],"module":[43],"concurrently":[45],"leverage":[46],"and":[49,130,135],"thereby":[52],"capturing":[53],"sufficient":[55],"feature.":[56],"Specifically,":[57],"for":[58],"given":[60],"pair":[61],"of":[62,106],"tasks,":[63,83],"compute":[65],"similarity":[68],"matrix":[69],"that":[70],"extracts":[71],"features":[74,89,94],"bidirectionally.":[75],"To":[76],"integrate":[77],"the":[78,86,91,102,122,139],"signals":[80],"from":[81],"different":[82,114],"fuse":[85],"with":[90,118],"corresponding":[92],"task-specific":[93],"using":[95],"an$1\\times":[96],"1$convolution.":[97],"Extensive":[98],"experimental":[99],"results":[100],"demonstrate":[101],"remarkable":[103],"performance":[104,148],"gain":[105],"our":[107,125],"method":[108,126],"two":[110],"challenging":[111],"datasets":[112],"w.r.t":[113],"task":[115],"sets,":[116],"compared":[117],"seven":[119],"approaches.":[120],"Under":[121],"two-task":[123],"setting,":[124,141],"has":[127],"achieved":[128],"1.63%":[129],"8.32%":[131],"improvements":[132],"NYUD-v2":[134],"PASCAL-Context,":[136],"respectively.":[137],"On":[138],"three-task":[140],"obtain":[143],"an":[144],"additional":[145],"7.7%":[146],"gain.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}