{"id":"https://openalex.org/W4364323035","doi":"https://doi.org/10.1109/tnnls.2023.3263335","title":"MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation","display_name":"MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation","publication_year":2023,"publication_date":"2023-04-10","ids":{"openalex":"https://openalex.org/W4364323035","doi":"https://doi.org/10.1109/tnnls.2023.3263335","pmid":"https://pubmed.ncbi.nlm.nih.gov/37037238"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3263335","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3263335","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5061737646","display_name":"Shenwang Jiang","orcid":"https://orcid.org/0000-0002-0914-4954"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenwang Jiang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0914-4954","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448292","display_name":"Jianan Li","orcid":"https://orcid.org/0000-0002-6936-9485"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianan Li","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6936-9485","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100726590","display_name":"Ying Wang","orcid":"https://orcid.org/0000-0002-6807-1513"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Wang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6807-1513","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101759485","display_name":"Wenxuan Wu","orcid":"https://orcid.org/0000-0002-5371-1186"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxuan Wu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043432751","display_name":"Jizhou Zhang","orcid":"https://orcid.org/0000-0002-1015-0534"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jizhou Zhang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1015-0534","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062250669","display_name":"Bo Huang","orcid":"https://orcid.org/0000-0001-6734-5247"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Huang","raw_affiliation_strings":["College of Optoelectronic Engineering, Chongqing University (CQU), Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-6734-5247","affiliations":[{"raw_affiliation_string":"College of Optoelectronic Engineering, Chongqing University (CQU), Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019242095","display_name":"Tingfa Xu","orcid":"https://orcid.org/0000-0001-5452-2662"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingfa Xu","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5452-2662","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4254,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60427743,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"35","issue":"9","first_page":"12494","last_page":"12506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973999857902527,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9955000281333923,"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/segmentation","display_name":"Segmentation","score":0.8369076251983643},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8108806610107422},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6711734533309937},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5597968101501465},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5566041469573975},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5362358093261719},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5016040802001953},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4897751808166504},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4891815483570099},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4587640166282654},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3964674472808838},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3810526728630066},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23287972807884216}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8369076251983643},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8108806610107422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6711734533309937},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5597968101501465},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5566041469573975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5362358093261719},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5016040802001953},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4897751808166504},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4891815483570099},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4587640166282654},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3964674472808838},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3810526728630066},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23287972807884216},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3263335","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3263335","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37037238","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37037238","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2218725766","display_name":null,"funder_award_id":"3040011182111","funder_id":"https://openalex.org/F4320327514","funder_display_name":"Beijing Institute of Technology Research Fund Program for Young Scholars"},{"id":"https://openalex.org/G4360217077","display_name":null,"funder_award_id":"62101032","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6928338148","display_name":null,"funder_award_id":"2021M690015","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G7797466398","display_name":null,"funder_award_id":"2022T150050","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320327514","display_name":"Beijing Institute of Technology Research Fund Program for Young Scholars","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1495267108","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1965287008","https://openalex.org/W1991367009","https://openalex.org/W2031489346","https://openalex.org/W2077865152","https://openalex.org/W2124351162","https://openalex.org/W2194775991","https://openalex.org/W2221898772","https://openalex.org/W2295107390","https://openalex.org/W2331300059","https://openalex.org/W2340897893","https://openalex.org/W2552414813","https://openalex.org/W2560023338","https://openalex.org/W2778764040","https://openalex.org/W2787091153","https://openalex.org/W2798376494","https://openalex.org/W2886773299","https://openalex.org/W2956648669","https://openalex.org/W2958537753","https://openalex.org/W2963091558","https://openalex.org/W2978409868","https://openalex.org/W2980189057","https://openalex.org/W2982361422","https://openalex.org/W3003882269","https://openalex.org/W3014641072","https://openalex.org/W3035600434","https://openalex.org/W3035680157","https://openalex.org/W3035716296","https://openalex.org/W3082755608","https://openalex.org/W3088431063","https://openalex.org/W3107695429","https://openalex.org/W3142871063","https://openalex.org/W3147190212","https://openalex.org/W3164177594","https://openalex.org/W3166152027","https://openalex.org/W3168479843","https://openalex.org/W3170128766","https://openalex.org/W3170581063","https://openalex.org/W3170841864","https://openalex.org/W3171581326","https://openalex.org/W3172949220","https://openalex.org/W3176692018","https://openalex.org/W3180003570","https://openalex.org/W3205981334","https://openalex.org/W3214910576","https://openalex.org/W4200284523","https://openalex.org/W4210346331","https://openalex.org/W4210476769","https://openalex.org/W4220971618","https://openalex.org/W4225608379","https://openalex.org/W4225636507","https://openalex.org/W4226069575","https://openalex.org/W4226360734","https://openalex.org/W4286908677","https://openalex.org/W4294310675","https://openalex.org/W4301462804","https://openalex.org/W6637373629","https://openalex.org/W6726497184","https://openalex.org/W6733814495","https://openalex.org/W6734824979","https://openalex.org/W6750523955","https://openalex.org/W6751647823","https://openalex.org/W6753772092","https://openalex.org/W6754568377","https://openalex.org/W6754756046","https://openalex.org/W6762718338","https://openalex.org/W6763430915","https://openalex.org/W6769066991","https://openalex.org/W7024286662"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W4205800335","https://openalex.org/W2371519352","https://openalex.org/W2386644571","https://openalex.org/W2372421320","https://openalex.org/W2901890255"],"abstract_inverted_index":{"Noisy":[0],"labels,":[1],"inevitably":[2],"existing":[3],"in":[4,46,86,182],"pseudo-segmentation":[5],"labels":[6,60],"generated":[7],"from":[8,140],"weak":[9],"object-level":[10],"annotations,":[11],"severely":[12],"hamper":[13],"model":[14,40,82,115,180],"optimization":[15],"for":[16,111,148,215],"semantic":[17,94,217],"segmentation.":[18,218],"Previous":[19],"works":[20],"often":[21],"rely":[22],"on":[23,188],"massive":[24],"handcrafted":[25],"losses":[26],"and":[27,38,145,193],"carefully":[28],"tuned":[29],"hyperparameters":[30],"to":[31,54,68,77,105,120,124,154,164],"resist":[32],"noise,":[33],"suffering":[34],"poor":[35],"generalization":[36],"capability":[37],"high":[39],"complexity.":[41],"Inspired":[42],"by":[43,135],"recent":[44],"advances":[45],"meta-learning,":[47],"we":[48,169],"argue":[49],"that":[50,98,177,197,204],"rather":[51],"than":[52],"struggling":[53],"tolerate":[55],"noise":[56,109],"hidden":[57],"behind":[58],"clean":[59,133],"passively,":[61],"a":[62,91,100,108,172,183,211],"more":[63],"feasible":[64],"solution":[65],"would":[66],"be":[67],"find":[69],"out":[70],"the":[71,150,156],"noisy":[72,126],"regions":[73,127],"actively,":[74],"so":[75],"as":[76,107],"simply":[78],"ignore":[79],"them":[80],"during":[81],"optimization.":[83],"With":[84],"this":[85,88],"mind,":[87],"work":[89],"presents":[90],"novel":[92],"meta-learning-based":[93],"segmentation":[95,114,151,167,195],"method,":[96],"MetaSeg,":[97],"comprises":[99],"primary":[101],"content-aware":[102],"meta-net":[103],"(CAM-Net)":[104],"serve":[106],"indicator":[110],"an":[112],"arbitrary":[113],"counterpart.":[116],"Specifically,":[117],"CAM-Net":[118],"learns":[119],"generate":[121],"pixel-wise":[122],"weights":[123],"suppress":[125],"with":[128],"incorrect":[129],"pseudo-labels":[130],"while":[131],"highlighting":[132],"ones":[134],"exploiting":[136],"hybrid":[137],"strengthened":[138],"features":[139],"image":[141],"content,":[142],"providing":[143],"straightforward":[144],"reliable":[146],"guidance":[147],"optimizing":[149],"model.":[152],"Moreover,":[153],"break":[155],"barrier":[157],"of":[158,205],"time-consuming":[159],"training":[160,175],"when":[161],"applying":[162],"meta-learning":[163],"common":[165],"large":[166],"models,":[168],"further":[170],"present":[171],"new":[173,212],"decoupled":[174],"strategy":[176],"optimizes":[178],"different":[179],"layers":[181],"divide-and-conquer":[184],"manner.":[185],"Extensive":[186],"experiments":[187],"object,":[189],"medical,":[190],"remote":[191],"sensing,":[192],"human":[194],"show":[196],"our":[198],"method":[199],"achieves":[200],"superior":[201],"performance,":[202],"approaching":[203],"fully":[206],"supervised":[207],"settings,":[208],"which":[209],"paves":[210],"promising":[213],"way":[214],"omni-supervised":[216]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}